Valuable insights into the thermospheric mass density and horizontal winds can be obtained from satellites equipped with accelerometers. To derive these quantities, radiation pressure must be accurately modeled and removed from the calibrated accelerometer measurements. However, the documented surface reflection and absorption coefficients, as well as the satellite’s thermal properties, are often inaccurate or, in some cases, even absent. This study presents a method for optimizing these parameters jointly with the accelerometer scale factors. Focusing on GRACE data from 2009, a case where radiation pressure was dominant over aerodynamic force, enabled us to refine the radiation pressure model without detrimental effects from errors in aerodynamic force modeling. We evaluated three variants of estimating the scale factor: estimating no accelerometer scale factors, only the y-axis scale factor, or both the y- and z-axis scale factors. We use the difference between the measured and modeled accelerations (the residual) as our target functional. Estimating both scale factors yielded the lowest residual for both GRACE satellites, even though the radiation pressure model was tuned using GRACE-A data only. After the optimization, we observed a systematic feature in the cross-track residuals within the geographical domain, which strongly correlates with the magnetic field vector experienced by the spacecraft. While its cause remains unknown, we introduced an empirical correction that effectively removed the feature and significantly increased consistency between GRACE-A and GRACE-B. Overall, we were able to reduce the RMS of the residuals by more than 13% in the cross-track direction and 32% in the radial direction, indicating a significant increase in modeling accuracy. The presented method provides a generalizable approach that can also be applied to future satellite missions with accelerometers.

The ESA GOCE satellite carried a gravity gradiometer consisting of three pairs of accelerometers on mutually orthogonal axes. For each accelerometer, bias and scale factors have been re-estimated by a dynamic precise orbit determination (POD) using improved gravity field modeling and standards. The kinematic orbit solution included in GPS-based Precise Science Orbit (PSO) product served as the baseline observables for 1210 daily arcs, covering the period from 1 November 2009 to 20 October 2013. Implementing improved force models almost completely resolved the deviations of the Y-axis scale factor obtained in earlier work (Visser and Ijssel 2016). A novel aspect is the verification by comparison with dynamic POD solutions based on SLR observations using 51 two-day orbital arcs. A high level of consistency was obtained between the kinematic PSO- and SLR-based accelerometer calibration parameters, e.g. within 0.01 nm/s2 for the X-axis pointing predominantly in the flight direction in terms of bias. One set of accelerometer scale factors was estimated for the entire mission. These were found to be consistent to within 0.005 for all accelerometer axes. The three-dimensional consistency between the dynamic orbits and the PSO reduced-dynamic orbit solutions has a mean Root-Mean-Square (RMS) of 4.5 and 10 cm, respectively, for the PSO reduced-dynamic and SLR-based dynamic orbit solutions. In addition, the one-dimensional RMS-of-fit of the PSO kinematic orbit solution improved significantly from 6.9 in Visser and Ijssel (2016) to 2.6 cm.

The Gravity Field and Steady-State Ocean Circulation Explorer (GOCE) satellite, which operated at an altitude of ∼250km, provided neutral thermosphere mass density and crosswind observations in the dawn-dusk sectors throughout most of its operational lifetime (2009–2013). As a result of its Sun-synchronous orbit, GOCE’s large solar panels remained at a near-perpendicular angle to the incoming solar radiation, leading to a significant radiation pressure acceleration. In this research, we focused on revisiting and reprocessing GOCE thermosphere mass density and crosswind data. We selected the coefficients describing the thermo-optical surface properties and employed a high-fidelity satellite geometry in a ray-racing simulation. Additionally, we distinguished between the solar flux in the visible and infrared bands and introduced a model for the satellite’s thermal emission. The availability of the in situ thermistor measurements allowed for the validation of the thermal model. Moreover, we replaced the Level-1b ion thruster data with raw telemetry, filling multiple data gaps. We analysed how incremental improvements in the radiation pressure modelling affected the observed crosswind speed. By replacing the panel model with the high-fidelity satellite geometry, the crosswind speed decreased up to 5 ms⁻¹. The biggest difference reduction of 40ms⁻¹resulted from introducing the thermal model. Splitting the solar flux further decreases the observed crosswind speed by up to 8ms⁻¹. The reduction in crosswind speed was most prominent during the first years of the mission when the solar activity was low. We compared the newly processed GOCE zonal wind data with respect to the most recent previous release. We observed a median absolute deviation decrease of 10 ms⁻¹around the south magnetic pole in the dawn sector. The yearly consistency of low-latitude zonal winds did not change significantly. The main obstacle in quantifying the improvement compared to the previous crosswind dataset stemmed from the fact that the previous and new datasets were generated with different crosswind estimation algorithms. The difference in thermosphere density compared to previously published datasets is minor since the effect of radiation pressure is most prominent in the cross-track direction. Finally, we verified the assumption about the energy accommodation coefficient of 0.82 and concluded that it remains valid after implementing the radiation pressure modelling improvements.

Traditional Global Navigation Satellite Systems (GNSSs) are subject to intentional or unintentional disturbances in the northern regions of Norway, leading to loss of critical infrastructure. The VHF Data Exchange System (VDES) has been suggested as an alternative source of positioning, navigation and timing (PNT), based on statistical estimates. However, an empirical investigation into the feasibility of such a contingency-system has only recently become possible after the launch of the NorSat-TD satellite with purpose-designed VDES ranging capabilities. This paper presents an analysis of the characteristics of empirical VDE-SAT range measurements and a system-level performance analysis of a single-satellite system. In total, 1121 VDE-SAT pseudorange observations obtained from 54 satellite passes, recorded from July to October 2023, are analyzed. Residual analysis shows that these observations have a large and constant mean error of about 416 km, with a standard deviation of 335.2 m. The previously neglected atmospheric propagation effects on a VDE-SAT range measurement are shown to be significant, and the largest effect is likely to be the time-delay due to the ionosphere. The system performance analysis shows that VDE-SAT as a PNT-source has potential to be a navigation backup system, with a target metric positioning accuracy of 1000 m. This project was funded by the ESA NAVISP program.

We investigate the climatology of Neutral Density Disturbances (NDDs) collocated with Equatorial Plasma Irregularities (EPIs) at altitudes above 450 km by using 20 years of data from the Gravity Recovery and Climate Experiment (GRACE) and GRACE-FO satellites. Electron density data are used to detect EPIs, and thermospheric neutral density measured onboard the same spacecraft serves to identify EPI-related NDDs. A detailed analysis focused on the morphological similarity between electron and neutral densities. To examine the relationship between EPI and NDD, statistical dependences of EPIs and NDDs on season/longitude (S/L), Magnetic Latitude (MLAT), Magnetic Local Time (MLT), and solar activity have been checked. As a first step, we confirmed that the EPI climatology in GRACE satellite data is consistent with previous reports. Then, it is found that the lower the neutral density in the background upper thermosphere, the higher the probability that EPI can accompany NDDs. We suggest that the vertical plasma advection surrounding EPI can result in neutral density disturbance, of which the efficiency depends on the background neutral scale height or temperature. The colder the thermosphere, the shorter its vertical scale height (or the lower the background neutral density), which can make the plasma advection leave measurable imprints on the neutral density.

Uncertainties in radiation pressure modelling play a significant role in the thermospheric density and crosswind observations derived from the GRACE-FO accelerometer, especially during low solar activity. Under such conditions, the radiation pressure acceleration matches the magnitude of the aerodynamic acceleration along the track and exceeds it in the cross-track direction. The GRACE-FO mission has been operating for several years at such high altitudes during both low and rising solar activity, providing a perfect opportunity to study the effects of radiation pressure. This research uses ray tracing based on a high-fidelity satellite geometry model to calculate the radiation pressure acceleration. We numerically fine-tuned the coefficients describing the thermo-optical surface properties to obtain more accurate radiation pressure accelerations than those specified in the GRACE-FO mission manual. We also used in situ temperature measurements from thermistors on the solar arrays to model the satellite's thermal emission. These temperature measurements allowed a realistic setup of the thermal model, extended by the parameter describing the efficiency of the solar cells, and reproduced the acceleration of the thermal emission with an accuracy of RMS 0.148 nms⁻². The combination of the updated thermal model and the fine-tuning of the surface coefficients improved the accuracy of the crosswind acceleration to an RMS of 0.55 nms⁻², compared to an RMS of 4.22 nms⁻² when using panel models and instantaneous thermal radiation. We compared the observed crosswind with two models: HWM14 and TIE-GCM. While both models capture most of the salient features of the observed crosswind, HWM14 shows particularly good agreement at high latitudes. Compared to the previously employed radiation pressure model, the crosswind observations have been improved in low and mid-latitudes, especially during periods of higher solar activity. Since the effect of radiation pressure is most significant in the crosswind direction, the effect on density was small compared to previously published datasets.

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.

We present new neutral mass density and crosswind observations for the CHAMP, GRACE, and GRACE-FO missions, filling the last gaps in our database of accelerometer-derived thermosphere observations. For consistency, we processed the data over the entire lifetime of these missions, noting that the results for GRACE in 2011- 2017 and GRACE-FO are entirely new. All accelerometer data are newly calibrated. We modeled the temperature-induced bias variations for the GRACE accelerometer data to counter the detrimental effects of the accelerometer thermal control deactivation in April 2011. Further, we developed a new radiation pressure model, which uses ray tracing to account for shadowing and multiple reflections and calculates the satellitea's thermal emissions based on the illumination history. The advances in calibration and radiation pressure modeling are essential when the radiation pressure acceleration is significant compared to the aerodynamic one above 450 km altitude during low solar activity, where the GRACE and GRACE-FO satellites spent a considerable fraction of their mission lifetime. The mean of the new density observations changes only marginally, but their standard deviation shows a substantial reduction compared to thermosphere models, up to 15% for GRACE in 2009. The mean and standard deviation of the new GRACE-FO density observations are in good agreement with the GRACE observations. The GRACE and CHAMP crosswind observations agree well with the physics-based TIE-GCM winds, particularly the polar wind patterns. The mean observed crosswind is a few tens of m·s-1 larger than the model one, which we attribute primarily to the crosswind errors being positive by the definition of the retrieval algorithm. The correlation between observed and model crosswind is about 60%, except for GRACE in 2004- 2011 when the signal was too small to retrieve crosswinds reliably.

Daedalus MASE (Mission Assessment through Simulation Exercise) is an open-source package of scientific analysis tools aimed at research in the Lower Thermosphere-Ionosphere (LTI). It was created with the purpose to assess the performance and demonstrate closure of the mission objectives of Daedalus, a mission concept targeting to perform in-situ measurements in the LTI. However, through its successful usage as a mission-simulator toolset, Daedalus MASE has evolved to encompass numerous capabilities related to LTI science and modeling. Inputs are geophysical observables in the LTI, which can be obtained either through in-situ measurements from spacecraft and rockets, or through Global Circulation Models (GCM). These include ion, neutral and electron densities, ion and neutral composition, ion, electron and neutral temperatures, ion drifts, neutral winds, electric field, and magnetic field. In the examples presented, these geophysical observables are obtained through NCAR’s Thermosphere-Ionosphere-Electrodynamics General Circulation Model. Capabilities of Daedalus MASE include: 1) Calculations of products that are derived from the above geophysical observables, such as Joule heating, energy transfer rates between species, electrical currents, electrical conductivity, ion-neutral collision frequencies between all combinations of species, as well as height-integrations of derived products. 2) Calculation and cross-comparison of collision frequencies and estimates of the effect of using different models of collision frequencies into derived products. 3) Calculation of the uncertainties of derived products based on the uncertainties of the geophysical observables, due to instrument errors or to uncertainties in measurement techniques. 4) Routines for the along-orbit interpolation within gridded datasets of GCMs. 5) Routines for the calculation of the global coverage of an in situ mission in regions of interest and for various conditions of solar and geomagnetic activity. 6) Calculations of the statistical significance of obtaining the primary and derived products throughout an in situ mission’s lifetime. 7) Routines for the visualization of 3D datasets of GCMs and of measurements along orbit. Daedalus MASE code is accompanied by a set of Jupyter Notebooks, incorporating all required theory, references, codes and plotting in a user-friendly environment. Daedalus MASE is developed and maintained at the Department for Electrical and Computer Engineering of the Democritus University of Thrace, with key contributions from several partner institutions.

Satellites in Low Earth Orbit (LEO) are essential for sounding the topside ionosphere. In this work, we present and validate a data set of Total Electron Content (TEC) and in situ electron density observations from the Gravity Recovery And Climate Experiment (GRACE) and GRACE-Follow-On missions as well as a TEC data set from the CHAllenging Minisatellite Payload mission. Concerning TEC, special emphasis is put to ensure optimal consistency to the already existing Swarm and Gravity field and steady-state ocean circulation explorer (GOCE) TEC data sets. The newly processed satellite missions allow covering two full solar cycles with LEO slant TEC. Furthermore, the twin satellite missions GRACE and GRACE-FO equipped with inter-satellite K-band ranging allows to derive the horizontal TEC and, due to the small inter-satellite distance of the satellite pairs, an approximation for local electron density. However, the derived value of electron density is relative and requires calibration using external information. In this work, the calibration is performed using the IRI-2016 model. Radar observations, as well as in situ electron density observations available from Swarm B Langmuir probes, are used for validation. Conjunctions between satellites are used to validate the TEC time series. The newly derived data set is shown to be highly consistent with the already existing data sets with standard deviations below 3 TECU for TEC (even 1 TECU was reached for low solar flux) and an offset below 7 × 10¹⁰ m⁻³ with a standard deviation near 1 × 10¹¹ m⁻³ for the electron density.

We statistically investigate fluctuation amplitudes (normalized to the background values) of dayside low-/mid-latitude upper-thermospheric mass density as observed by the Gravity Recovery and Climate Experiment (GRACE) and GRACE-Follow-On (GRACE-FO) spacecraft at ∼500 km altitude between 2002 and 2022. There are three new findings in our results. First, the climatology closely replicates previous studies on stratospheric and upper-thermospheric gravity waves (GWs) below the GRACE(-FO) altitudes. For example, in low-latitude regions, the fluctuations are stronger above continents than in the oceanic area. Mid-latitude fluctuations prefer the local winter hemisphere to the summer, and the South American/Atlantic region in June solstice hosts stronger fluctuations than in any other low-/mid-latitude locations or seasons. Fluctuations are more intense under lower solar activity. The above-mentioned consistency of the GRACE(-FO) results with previous lower-altitude GW studies confirms that GWs can penetrate up to 500 km. Second, the anti-correlation of upper-thermospheric GW with solar activity, which has been earlier reported for multi-year time scales, can also be identified on the scale of the solar rotation period (∼27 days). Third, we demonstrate asymmetry between pre-noon and post-noon GWs. The former exhibits stronger GW activity, which may result from the colder thermosphere being more favorable for intense mass density fluctuations via secondary/tertiary GW generation.

Cold Atom technology has undergone rapid development in recent years and has been demonstrated in space in the form of cold atom scientific experiments and technology demonstrators, but has so far not been used as the fundamental sensor technology in a science mission. The European Space Agency therefore funded a 7-month project to define the CASPA-ADM mission concept, which serves to demonstrate cold-atom interferometer (CAI) accelerometer technology in space. To make the mission concept useful beyond the technology demonstration, it aims at providing observations of thermosphere mass density in the altitude region of 300–400 km, which is presently not well covered with observations by other missions. The goal for the accuracy of the thermosphere density observations is 1% of the signal, which will enable the study of gas–surface interactions as well as the observation of atmospheric waves. To reach this accuracy, the CAI accelerometer is complemented with a neutral mass spectrometer, ram wind sensor, and a star sensor. The neutral mass spectrometer data is considered valuable on its own since the last measurements of atmospheric composition and temperature in the targeted altitude range date back to 1980s. A multi-frequency GNSS receiver provides not only precise positions, but also thermosphere density observations with a lower resolution along the orbit, which can be used to validate the CAI accelerometer measurements. In this paper, we provide an overview of the mission concept and its objectives, the orbit selection, and derive first requirements for the scientific payload.

Exospheric temperature is one of the key parameters in constructing thermospheric models and has been extensively studied with in situ observations and remote sensing. The Global-scale Observations of the Limb and Disk (GOLD) at a geosynchronous vantage point provides dayglow limb images for two longitude sectors, from which we can estimate the terrestrial exospheric temperature since 2018. In this paper, we investigate climatological behavior of the exospheric temperature measured by GOLD. The temperature has positive correlations with solar and geomagnetic activity and exhibits a morning-afternoon asymmetry, both of which agree with previous studies. We have found that the arithmetic sum of F_10.7 (solar) and Ap (geomagnetic) indices is highly correlated with the exospheric temperature, explaining ∼64% of the day-to-day variability. Furthermore, the exospheric temperature has good correlation with thermospheric parameters (e.g., neutral temperature, O₂ density, and NO emission index) sampled at various heights above ∼130 km, in spite of the well-known thermal gradient below ∼200 km. However, thermospheric temperature at altitudes around 100 km is not well correlated with the GOLD exospheric temperature. The result implies that effects other than thermospheric heating by solar Extreme Ultraviolet and geomagnetic activity take control below a threshold altitude that exists between ∼100 and ∼130 km.

The satellite acceleration data from the CHAMP, GRACE, GOCE, and Swarm missions provide detailed information on the thermosphere density over the last two decades. Recent work on reducing errors in modelling the spacecraft geometry has greatly reduced scale differences between the thermosphere data sets from these missions. However, residual inconsistencies between the data sets and between data and models are still present. To a large extent, these differences originate in the modelling of the gas-surface interactions (GSI), which is part of the satellite aerodynamic modelling used in the acceleration to density data processing. Physics-based GSI models require in-situ atmospheric composition and temperature data that are not measured by any of the above-mentioned satellites and, as a consequence, rely on thermosphere models for these inputs. To reduce the dependence on existing thermosphere models, we choose a GSI model with a constant energy accommodation coefficient per mission, which we optimize exploiting particular attitude manoeuvres and wind analyses to increase the self-consistency of the multi-mission thermosphere mass density data sets. We compare our results with those based on variable energy accommodation obtained by different studies and semi-empirical models to show the principal differences. The presented comparisons provide novel opportunity to quantify the discrepancies between current GSI models. Among the presented data, density variations with variable accommodation are within ±10%, and peaks can reach up to 15% at the poles. The largest differences occur during low solar activity periods. In addition, we utilize a series of attitude manoeuvres performed in May 2014 by the Swarm A and C satellites, which are flying in close proximity, to evaluate the residual inconsistency of the density observations as a function of the energy accommodation coefficient. Our analysis demonstrates that an energy accommodation coefficient of 0.85 maximizes the consistency of the Swarm density observations during the attitude manoeuvres. Using such coefficient, for Swarm A and Swarm C, the new density would be lower in magnitude with a 4-5% difference. In recent studies, similar energy accommodation coefficients were retrieved for the CHAMP and GOCE missions by investigating thermospheric winds. These new values for the energy accommodation coefficient provide a higher consistency among different missions and models. A comparison of neutral densities between current thermosphere models and observations indicates that semi-empirical models such as NRLMSISE-00 and DTM-2013 significantly overestimate the density, and that an overall higher consistency between the observations from the different missions can be achieved with the presented assumptions. The new densities from this work provide consistencies of 4.13% and 3.65% between the minimum and maximum mean ratios among the selected missions with NRLMSISE-00 and DTM-2013, respectively. A comparison with the WACCM-X general circulation model is also performed. Similar to the other models, WACCM-X seems to provide higher estimates of mass density especially under high and moderate solar activities. This work has the objective to guide density data users over the multiple data sets and highlight the remaining uncertainties associated with different GSI models.

The lower-Thermosphere-ionosphere (LTI) system consists of the upper atmosphere and the lower part of the ionosphere and as such comprises a complex system coupled to both the atmosphere below and space above. The atmospheric part of the LTI is dominated by laws of continuum fluid dynamics and chemistry, while the ionosphere is a plasma system controlled by electromagnetic forces driven by the magnetosphere, the solar wind, as well as the wind dynamo. The LTI is hence a domain controlled by many different physical processes. However, systematic in situ measurements within this region are severely lacking, although the LTI is located only 80 to 200 km above the surface of our planet. This paper reviews the current state of the art in measuring the LTI, either in situ or by several different remote-sensing methods. We begin by outlining the open questions within the LTI requiring high-quality in situ measurements, before reviewing directly observable parameters and their most important derivatives. The motivation for this review has arisen from the recent retention of the Daedalus mission as one among three competing mission candidates within the European Space Agency (ESA) Earth Explorer 10 Programme. However, this paper intends to cover the LTI parameters such that it can be used as a background scientific reference for any mission targeting in situ observations of the LTI.

Space weather phenomena such as scintillations of Global Navigation Satellite Systems (GNSS) signals are of increasing importance for aviation, the maritime, and civil engineering industries. The ionospheric plasma irregularities causing scintillations are associated with strong gradients in ionospheric plasma density. To provide nowcasts and forecasts of space weather effects, it is vital to monitor the ionosphere and detect strong density variations. To reconstruct plasma density variations in the polar cap ionosphere, we use total electron content (TEC) estimates from the Swarm satellites' GPS receivers. By considering events where the Swarm satellites are in close proximity, we obtain plasma density variations by inverting TEC measurements on a two-dimensional grid. We first demonstrate the method using synthetic test data, before applying it to real data. The method is validated using in situ Langmuir probe measurements and ground-based TEC observations. We find that the new method can reproduce density variations, although it is sensitive to the geometry of the Swarm satellite constellation and to the calculated plasma temperature. Our proposed method opens new possibilities for ionospheric plasma monitoring that uses GPS receivers aboard low Earth orbit (LEO) satellites.