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The atmospheric pressure and density are important factors affecting the water entry cavity and load characteristics of the vehicle. However, it is difficult to take into account the equivalent simulation of the two in the scaled-down test. The use of atmospheric pressure–density two-parameter compensation may become a key means to achieve accurate scale similarity. In this paper, the evolution of the water entry cavity and the similarity of impact loads for multiscale models in different environments are studied. Aiming at the problem that the similarity conditions are difficult to meet in small-scale model test, a distortion compensation correction method is proposed. The results show that under normal pressure environment, as the scale ratio decreases, the cavity surface closes in advance, and the slamming load gradually decreases. Under reduced pressure environment, the influence of the "scale effect" is significantly reduced. As the pressure decreases, the cavity surface closure phenomenon is weakened, and the cushioning effect of the air cushion is reduced, resulting in an increase in the slamming load. Quantitative analysis shows that the atmospheric pressure mainly affects the pressure disturbance trend in the cavity, while the atmospheric density determines the scale of the cavity and the size of the model load. By adjusting the pressure and density parameters, the prediction deviation of the small-scale model test on the disturbance time of the prototype reentrant jet pressure can be controlled within 2.4%. [ABSTRACT FROM AUTHOR]

The water entry cavity and load characteristics obtained through scaled-down tests are correlated with the atmospheric pressure and density at the free surface. The evaluation of the influence of the cavitation number and atmospheric density coefficient is highly essential for scale tests to improve the prototype prediction accuracy. Focusing on the similarity criterion simulations and load prediction of the scaled-down tests, this study conducts the simulation tests of the water entry characteristics of the scaled-down model under different environments: normal pressure, reduced pressure, and reduced pressure and heavy gas replacement. Moreover, the influence of the cavitation number and atmospheric density coefficient on the multiphase flow, slamming load, and air cushion effect is discussed. The "air cushion effect" is formed at the top of the vehicle during water entry process, which affects the peak narrow pulse width slamming load. Furthermore, the "air cushion" experiences expansion–stability–rupture–escape with increasing water invasion depth. As the atmospheric pressure decreases, the gas tends to thin and the retention inertia weakens. The decrease in the "air cushion" buffering capacity leads to the increase in the slamming load and the expansion of the cavity scale formed by the liquid. Excessive simulation of the dynamic pressure results in the delayed closure of the cavity surface and the slow fall of the water curtain. As the atmospheric density increases, the retention inertia of gas increases because of the increase in the molecular mass, the slamming load gradually decreases, and the closure time of the cavitation and water curtain decreases. The research results of this paper provide some reference for the similarity transformation of the scaled-down test and the pre-research of the prototype. [ABSTRACT FROM AUTHOR]

We report on the recent earthquakes (EQs) that occurred, with the main shock on 6 February 2023, principally in the central southern part of Turkey and northwestern Syria. This region is predisposed to earthquakes because of the tectonic plate movements between Anatolian, Arabian, and African plates. The seismic epicenter was localized at 37.08°E and 37.17°N with depth in the order of 10 km and magnitude Mw7.8. We use Graz's very-low-frequency VLF facility (15.43°E, 47.06°N) to investigate the amplitude variation in the Denizköy VLF transmitter, localized in the Didim district of Aydin Province in the western part of the Anatolian region in Turkey. Denizköy VLF transmitter is known as Bafa transmitter (27.31°E, 37.40°N), radiating at a frequency of 26.7 kHz under the callsign TBB. This signal is detected daily by the Graz facility with an appropriate signal-to-noise ratio, predominantly during night observations. We study in this analysis the variations of TBB amplitude and phase signals as detected by the Graz facility two weeks before the earthquake occurrence. It is essential to note that the TBB VLF transmitter station and the Graz facility are included in the preparation seismic area, as derived from the Dobrovolsky relationship. We have applied the multi-terminators method (MTM), revealing anomalies occurring at sunset and sunrise terminator occasions and derived from the amplitude and the phase. Minima and maxima of the TBB signal are linked to three terminators, i.e., Graz facility, TBB transmitter, and EQ epicenter, by considering the MTM method. We show that the significant anomalies are those linked to the EQ epicenter. This leads us to make evident the precursor seismic anomaly, which appears more than one week (i.e., 27 January 2023) before EQ occurrence. They can be considered the trace, the sign, and the residue of the sub-ionospheric propagation of the TBB transmitter signal disturbed along its ray path above the preparation EQ zone. We find that the sunrise–sunset anomalies are associated with tectonic regions. One is associated with the Arabian–African tectonic plates with latitudinal stresses in the south–north direction, and the second with the African–Anatolian tectonic plates with longitudinal stresses in the east–west direction. The terminator time shift anomalies prior to EQ are probably due to the lowering (i.e., minima) and raising (i.e., maxima) of the ionospheric electron density generated by atmospheric gravity waves. [ABSTRACT FROM AUTHOR]

Thermospheric density influences the atmospheric drag and is crucial for space missions. This paper introduces a global thermospheric density prediction framework based on a deep evidential method. The proposed framework predicts thermospheric density at the required time and geographic position with given geomagnetic and solar indices. It is called global to differentiate it from existing research that only predicts density along a satellite orbit. Through the deep evidential method, we assimilate data from various sources including solar and geomagnetic conditions, accelerometer‐derived density data, and empirical models including the Jacchia‐Bowman model (JB‐2008) and the Naval Research Laboratory Mass Spectrometer and Incoherent Scatter Radar Extended (NRLMSISE‐00) model. The framework is investigated on five test cases along various satellites from 2003 to 2015 involving geomagnetic storms with Disturbance Storm Time (Dst) values smaller than −50 nT $\mathrm{n}\mathrm{T}$. Results show that the proposed framework can generate density with higher accuracy than the two empirical models. It can also obtain reliable uncertainty estimations. Global density estimations at altitudes from 200 to 550 km are also presented and compared with empirical models on both quiet and storm conditions. Plain Language Summary: Thermospheric density affects atmospheric drag, which is important for many space missions. This paper presents a global thermospheric density prediction framework based on a deep evidential method. It incorporates data from empirical models JB‐2008 and NRLMSISE‐00, solar and geomagnetic indices, and density derived from satellite accelerometers. Test cases are designed from 2003 to 2015 under quiet and storm conditions based on various satellites. The proposed framework demonstrates higher accuracy and reliable uncertainty estimates compared to the empirical models. Key Points: A global thermospheric density prediction framework is presented based on a deep evidential methodThe proposed framework predicts thermospheric density at the required time and geographic position with given geomagnetic and solar indicesThe proposed framework predicts thermospheric density more accurately than two empirical models and provides reliable uncertainty estimations [ABSTRACT FROM AUTHOR]

Meteoroids of sub‐milligram sizes burn up high in the Earth's atmosphere and cause streaks of plasma trails detectable by meteor radars. The altitude at which these trails, or meteors, form depends on a number of factors including atmospheric density and the astronomical source populations from which these meteoroids originate. A previous study has shown that the altitude of these meteors is affected by long‐term linear trends and the 11‐year solar cycle related to changes in our atmosphere. In this work, we examine how shorter diurnal and seasonal variations in the altitude distribution of meteors are dependent on the geographical location at which the measurements are performed. We use meteoroid altitude data from 18 independent meteor radar stations at a broad range of latitudes and investigate whether there are local time (LT) and seasonal variations in the altitude of the peak meteor height, defined as the majority detection altitude of all meteors within a certain period, which differ from those expected purely from the variation in the visibility of their astronomical source. We find a consistent LT and seasonal response for the Northern Hemisphere locations regardless of latitude. However, the Southern Hemisphere locations exhibit much greater LT and seasonal variation. In particular, we find a complex response in the four stations located within the Southern Andes region, which indicates that the strong dynamical atmospheric activity, such as the gravity waves prevalent here, disrupts, and masks the seasonality and dependence on the astronomical sources. Plain Language Summary: Small meteoroids burn up high in the Earth's atmosphere producing trails of plasma detectable by ground‐based meteor radar instruments. The altitude at which these trails occur depends on a number of factors including atmospheric density and the astronomical source populations from which these meteoroids originate. Previous work demonstrated that the altitude at which the majority of these meteoroids burn up (termed "peak meteor altitude") is affected by long‐term atmospheric changes, such as those related to greenhouse gas emissions and the 11‐year solar cycle. Here, we focus on shorter timescales and analyze meteoroid altitude data from 18 geographically diverse meteor radars to examine the local time (LT) and seasonal variation in the peak meteor altitudes on a latitude basis. We find a consistent LT and seasonal response among the six Northern Hemisphere meteor radar station locations irrespective of latitude. However, we find a more complex response among the 12 Southern Hemisphere stations with much greater LT and seasonal variation. In particular, we found a complex response in the four stations located within the Southern Andes region, a geographic region known for intense atmospheric gravity wave activity, which acts to mask and disrupt the seasonality and dependence on the astronomical sources. Key Points: Local time (LT) and seasonal variations in the peak meteor height exist, which differ from those expected from astronomical variation aloneThere is a consistent LT and seasonal response in the Northern Hemisphere locations regardless of latitudeA complex response in the Andes region where a strong gravity wave component acts to mask seasonality and dependence on astronomical sources [ABSTRACT FROM AUTHOR]

Satellites in very low Earth orbits can leverage the aerodynamics forces for control purposes. Three-axis attitude control can be achieved by adjusting the orientation of aerodynamic surfaces, benefiting from both drag and lift forces. However, complete control over the orbital motion of a satellite is unattainable using aerodynamic forces alone, as positive thrust cannot be generated. Nonetheless, this limitation does not apply when focusing on the control of a satellite formation. By properly modulating the orientation of panels, positive and negative relative forces can be generated. This paper shows that even in a formation of simple microsatellites, it is possible to achieve formation and attitude simultaneous control by using no other actuators than the aerodynamics surfaces. • Very Low Earth orbits are appealing but the large atmospheric density can be a problem. • The atmospheric forces can be used for control purposes. • Formation control and attitude control can be individually realized by using aerodynamic forces. • A GNC architecture is implemented to realized both goals with the same aerodynamic actuators. • Performance in keeping or acquiring a desired state (attitude and relative position) is promising. [ABSTRACT FROM AUTHOR]

The low-Earth-orbit (LEO) environment will likely experience an exponential growth of the anthropogenic space object population, also due to the many proposed large constellations, which could negatively affect the sustainability of the space environment if no proper regulatory actions are introduced. This paper introduces a methodology to analyze high-capacity sustainable solutions of the LEO region from 200 to 900 km altitude. Sustainability is assessed through the stable equilibrium points of a source-sink model called MIT Orbital Capacity Assessment Tool 3 (MOCAT-3). Capacity is estimated using an optimization procedure that aims to compute the optimal launch rate that maximizes the number of satellites in LEO, subject to a risk-rate constraint. Results show that the sustainable number of satellites increases with the risk rate constraint. Moreover, the resilience of the proposed solutions is tested against a more accurate time-varying atmospheric density model and perturbations of the initial equilibrium population. The compatibility of the proposed solutions with future traffic launches and a strategy to accommodate future traffic needs are presented. Limitations of the current work are discussed, chiefly the importance of validation of model coefficients and behavior before resulting capacity estimates are used to guide actual decision-making. [ABSTRACT FROM AUTHOR]

Low-Earth-orbit (LEO) spacecraft are significantly influenced by atmospheric drag. Accurately estimating thermospheric density is pivotal for the precise calculation of drag acceleration. However, thermospheric density along a specific orbit, computed using existing thermospheric models, has certain inaccuracies. In this work, a first-order Gauss-Markov process is used to model the deviation of atmospheric drag acceleration. With the Markov parameter of the initial state iteratively computed through sequential estimation and the smoothing method, the thermospheric density is derived from high-precision GPS measurements. In simulation scenarios, the root-mean-square error and relative error of the estimated thermospheric density reduce by about 45 and 50% relative to the prior density, respectively. Using the estimated density for orbit propagation, satellite trajectories' one-day position and velocity error are, respectively, within 100 m and 0.1 m/s, and an average improvement in orbit precision is over 80%. The proposed method has been applied to the real Tsinghua Science Satellite (Q-SAT) GPS measurements for effectiveness verification. It shows strong adaptability under extreme space weather and during the occurrence of geomagnetic storms. Due to the estimated Markov parameter of the initial state obeying the Langevin dynamics properties, the proposed method also offers short-term thermospheric density forecasting potential. [ABSTRACT FROM AUTHOR]

Satellite drag coefficients are crucial for determining the neutral mass densities that affect spacecraft operations in the thermosphere. Many studies typically utilize a constant drag coefficient of 2.2 to calculate the neutral density. However, due to the variability of space environment, uncertainties in the drag coefficient can lead to significant systematic discrepancies in neutral density measurements. Satellite drag coefficient may fluctuate in the thermosphere under various geomagnetic activities and altitudes. For the first time, we calculate the spherical satellite drag coefficient using data from the "Orbital Atmospheric Density Detection Experimental Satellite," referred to as the QX satellite. Our findings reveal that the drag coefficient can be estimated by thermospheric temperature and density, which are dependent on geomagnetic activity and altitude. At an altitude of ∼510 km, drag coefficients are adjusted to around 2.425, instead of the constant value of 2.2. Furthermore, the drag coefficient may decrease due to the significant influence of increasing geomagnetic activity, such as geomagnetic storms, on thermospheric density and temperature. These estimates of the drag coefficient can also be used to reduce discrepancies when deducing the ballistic coefficient. Consequently, using the estimated drag coefficient can accurately determine the QX‐derived neutral density, which agrees well with the density from Swarm‐B satellite. Plain Language Summary: Satellite drag coefficient is a key factor in advancing space engineering and understanding the impacts of space weather conditions on satellites in the thermosphere. It helps in calculating the neutral mass density associated with atmospheric drag force and estimating the satellite orbital lifetime. In this study, it is the first time calculating the spherical satellite drag coefficient using data from QX satellite, collected from 28 July 2022 to 30 June 2023. We investigate the response of the drag coefficient to thermospheric temperature and density under different geomagnetic activities and altitudes. These relationships allow us to estimate the spherical satellite drag coefficient, which in turn helps us improve the accuracy of determining the ballistic coefficient and the corresponding neutral mass density. Compared with the results of the drag constant of 2.2, the QX‐derived densities determined using the estimated drag coefficients, align well with the in‐situ observations from Swarm Precise Orbit Determination data. Overall, our results enhance the understanding of how the spherical satellite drag coefficient changes in response to variations in the thermosphere under different space weather conditions. We also suggest a method for estimating the drag coefficient, which has valuable applications in the calculation of neutral mass density. Key Points: We put forward a new method for determining drag coefficients using temperature and density affected by geomagnetic activity and altitudeGeomagnetic activity increases, associated with the enhancements in temperature and density, leading to a reduction of the drag coefficientUsing the estimated drag coefficients allows for accurate determination of QX‐derived density, which aligns well with Swarm‐derived density [ABSTRACT FROM AUTHOR]

The Stimson formation is a late‐infilling eolian sandstone in Gale crater, Mars that formed from sand accumulation in a dune field analogous to the modern active Bagnold dune field, enabling a unique opportunity to compare the past to the present dune fields on Mars. Previous work suggested that the Stimson has a coarser grain‐size distribution than the active Bagnold dunes based on three images of the Stimson. We analyze grain size in the Naukluft and Emerson plateaus of the Stimson by observing 115 images throughout the formation to classify textures and quantitatively measuring grains in eight representative individual images. Results indicate that the Stimson has a primary grain size mode at <200 μm. In addition, more than 50% of the observed Stimson rock targets display a coarser grain population with a long‐tailed distribution including grains ∼600–1200 μm. The primary grain size mode is similar to that observed in the Bagnold dunes, but the coarse grain size mode was neither observed in the Bagnold dunes nor in ripples adjacent to the dune field. Models for saltation mechanics indicate that the favored grain size for eolian transport on Mars, ∼100–200 μm, is independent of atmospheric density, though atmospheric density affects the wind speeds at which grains can be transported by winds. We conclude that the source of the Stimson dunes was more proximal and coarser than the source of the Bagnold dunes and that the paleoatmosphere was likely not significantly denser than the modern Martian atmosphere. Plain Language Summary: The Curiosity rover on Mars observed ancient cemented sand‐dune deposits called the Stimson formation near the modern and active Bagnold dunes. These observations provide a unique opportunity to compare past and present environments on Mars. Here, we present measurements of the size of sand grains in the Stimson deposits to compare with previously published measurements of the active Bagnold sands. We minimize bias by using observations from two cameras to find proportionate contributions of texture groups and quantify grain sizes for each texture group. We find that more than half of the images of Stimson deposits contain grains that are coarser than the coarsest grains observed near the modern sand dunes. Previous work hypothesized that these coarser grains could imply that the Stimson dunes formed under either a denser or a thinner atmosphere. We use sediment transport theory and observations to show that the atmosphere was likely similar to modern Mars. Instead, the coarse grains reveal that there must have been a supply of coarse grains nearby when the Stimson dunes formed, likely from eroding riverbeds. Cementation of the Stimson dunes required the presence of liquid water and may thus have required a denser atmosphere, possibly indicating cyclic atmospheric changes through time. Key Points: Comparing ancient and modern windblown sediments enables the study of Mars' eolian environments through timeAbout half of the targets in the Stimson sandstone contain a coarse fraction of grains (>500 μm) that is not observed in the modern Bagnold dunesThe presence of coarse grains in the Stimson necessitates a proximal coarse‐grained source [ABSTRACT FROM AUTHOR]

We present X‐ray observations of the upper atmospheric density disturbance caused by the explosive eruption of the Hunga Tonga‐Hunga Ha'apai (HTHH) volcano on 15 January 2022. From 14 January to 16 January, the Chinese X‐ray astronomy satellite, Insight‐HXMT, was observing the supernova remnant Cassiopeia A. The X‐ray data obtained during Earth's atmospheric occultations allowed us to measure neutral densities in the altitude range of ∼ ${\sim} $90–150 km. The density profiles above 110 km altitude obtained before the major eruption are in reasonable agreement with expectations by both GAIA and NRLMSIS 2.0 models. In contrast, after the HTHH eruption, a severe density depletion was found up to 1,000 km away from the epicenter, and a relatively weak depletion extending up to ∼7,000 ${\sim} 7,000$ km for over 8 hr after the eruption. In addition, density profiles showed wavy structures with a typical length scale of either ∼ ${\sim} $20 km (vertical) or ∼ ${\sim} $1,000 km (horizontal). This may be caused by Lamb waves or gravity waves triggered by the volcanic eruption. Plain Language Summary: Volcanic eruptions trigger acoustic and gravity waves that propagate vertically upward and cause significant perturbations in the ionosphere. Lots of observations revealed ionospheric disturbances. However, there have been limited observations of the mesosphere and the lower thermosphere (MLT)—an important atmospheric layer that connect the ionospheric disturbances and the volcanic eruption. On 15 January 2022, a huge explosive eruption occurred at Hunga Tonga‐Hunga Ha'apai (HTHH), providing us with excellent opportunities to study the atmosphere‐ionosphere disturbances driven by volcanic eruptions. Here, we first reveal MLT neutral density disturbances caused by the HTHH eruption, based on atmospheric occultations of the celestial X‐ray bright source, Cassiopeia A, observed with the Chinese X‐ray astronomy satellite Insight‐HXMT. Shortly after the HTHH eruption, we found severe density depletions in the vicinity of the epicenter, by factors of ∼ ${\sim} $2–10 less than the control experiments by two atmospheric models. The strongest density depletion was found at 500–1,000 km away from the epicenter, and a relatively weak depletion extends up to ∼ ${\sim} $7,000 km for at least 8 hr after the eruption. This density behavior is qualitatively consistent with that seen at a much higher altitude of ∼ ${\sim} $500 km. In addition, neutral density profiles obtained in the MLT suggest a typical length scale of either ∼ ${\sim} $20 km (vertical) or ∼ ${\sim} $1,000 km (horizontal). This may be caused by Lamb waves or gravity waves triggered by the volcanic eruption. This study demonstrates the power of the X‐ray remote sensing technique to investigate little‐known behaviors of the MLT. Key Points: Neutral density profiles in the MLT were measured before and after Tonga's huge volcanic eruption on 15 January 2022Shortly after the eruption, a strong and long‐lasting neutral density depletion was found near the epicenterDensity profiles after the eruption showed wavy structures with a typical wavelength of either ∼20 km (vertical) or ∼1,000 km (horizontal) [ABSTRACT FROM AUTHOR]

A fast and accurate radiative transfer model is the prerequisite in the field of atmospheric remote sensing for limb atmospheric inversion to tackle the drawback of slow calculation speed of traditional atmospheric radiative transfer models. This paper established a fast computing model (ANN-HASFCM) for high-spectral-resolution absorption spectra by using artificial neural networks and PCA (principal component analysis) spectral reconstruction technology. This paper chose the line-by-line radiative transfer model (LBLRTM) as the comparative model and simulated training spectral data in the oxygen A-band (12,900–13,200 cm−1). Subsequently, ANN-HASFCM was applied to the retrieval of the atmospheric density profile with the data of the Global Ozone Monitoring by an Occultation of Stars (GOMOS) instrument. The results show that the relative error between the optical depth spectra calculated by LBLRTM and ANN-HASFCM is within 0.03–0.65%. In the process of using the global-fitting algorithm to invert GOMOS-measured atmospheric samples, the inversion results using Fast-LBLRTM and ANN-HASFCM as forward models are consistent, and the retrieval speed of ANN-HASFCM is more than 200 times faster than that of Fast-LBLRTM (reduced from 226.7 s to 0.834 s). The analysis shows the brilliant application prospects of ANN-HASFCM in limb remote sensing. [ABSTRACT FROM AUTHOR]

In this study the electron density of an atmospheric plasma generated between a pin electrode and a water surface is measured by determining the Stark broadening of H α and H β emission lines. Comparable values for the electron density are achieved using the H α and H β broadening obtained in separate measurements. During the temporally evolving system, increasing electron densities are measured of 0.5 − 3 ⋅ 10 15 cm−3 during the plasma treatment of 5–10 min. The effect of the water temperature on plasma-water interaction is investigated by heating the water to ≈ 70 ∘ C prior to the measurements. This resulted in higher gas temperatures during the discharge up to 2500 K and 4000 K for positively and negatively pulsed discharge, respectively. Furthermore, an earlier increase of electron density and conductivity of the water is measured for the preheated experiments. The humidity of the gas is likely to be an important parameter causing the observed results. [ABSTRACT FROM AUTHOR]

Hydrogen, with its unique flammability characteristics, demands additional consideration due to its broader flammable range compared to fossil fuels. Its low density at atmospheric conditions results in significant buoyancy, mitigating risks in outdoor applications. In confined spaces, hydrogen releases can lead to flammable cloud formation. To study this problem, independent of its dimensions, a dimensional analysis is introduced based on Buckingham's Π -theorem. This work focuses on thirteen functional parameters, including mole fraction, time, release velocity, orifice diameter, reduced gravity, molecular mass diffusion, viscosity and geometric dimensions. Four dimensional scenarios are simulated and compared in this study, to assess the adequacy of the proposed non-dimensional approach. The setup involves a parallelepiped enclosure with a single release point. RANS simulations are conducted. The proposed non-dimensional formulation proves valuable for interpreting data and discussing practical applications. The study contributes to a deeper understanding of hydrogen filling regimes in confined spaces, offering insights for safety assessments and risk mitigation strategies. [Display omitted] • Functional parameters for hydrogen distribution are proposed. • Application of Buckingham's Π -theorem yields essential non-dimensional ratios. • RANS CFD-model used to simulate and discuss four similar scenarios. • Time series analysis of non-dimensional flammable volume reveals similarity. • Ratios and non-dimensional flammable volume enable dimension-independent safety analysis. [ABSTRACT FROM AUTHOR]

A significant challenge for interplanetary small satellites is fully propulsive orbit insertion due to limited total velocity change capabilities. At destinations with significant atmospheres, this challenge can be circumvented via aerocapture, a technique that uses a single atmospheric pass to convert a hyperbolic approach trajectory into a captured elliptical orbit. This paper investigated small satellite aerocapture at Mars with the morphable entry system, a deployable entry vehicle concept that uses shape morphing for trajectory control. A Monte Carlo dispersion analysis was conducted to assess the vehicle's robustness with respect to uncertainties in entry state, atmospheric density, and vehicle aerodynamics. Under the combined effects of these uncertainties, the morphable entry system achieved a 100% aerocapture success rate. Furthermore, the total velocity change required to place the vehicle on the target orbit for 99% of the simulated trajectories was 166.5 m/s, which is within the current capabilities of small satellite propulsion systems. The results suggest that the morphable entry system is a viable option for smallsat aerocapture at Mars. • Morphable entry system (MES) uses shape-morphing for aerocapture trajectory control. • MES achieved 100% aerocapture success rate at Mars. • MES may be a viable option for small satellite aerocapture at Mars. [ABSTRACT FROM AUTHOR]

With the proliferation of low Earth orbit (LEO) satellites carrying GNSS receivers on‐board commercial operators such as Spire, Starlink, OneWeb, and Amazon, an abundance of high‐cadence tracking data could become available to the scientific community. While GNSS measurements from geodetic‐grade receivers on satellites like SWARM, CHAMP, GRACE, and GOCE have been extensively used for atmospheric density retrieval, limited research has explored the potential of less accurate data from commercial operators. This study focuses on two methods to estimate atmospheric densities from precision orbit determination (POD) products—precise positions and velocities—utilizing synthetic data sets. The first method, termed "POD accelerometry" treats the POD products as measurements to a reduced‐dynamic POD scheme with the goal of estimating densities using stochastic parameters. The second method known as the energy dissipation rate (EDR) approach derives densities from changes in orbital energy. The relative contributions of various error sources—dynamics model uncertainties, and POD noise—to the estimated densities are studied for a limited set of orbital regimes and space weather activity, and possible error mitigation strategies are suggested. The performance of the two methods and their sensitivities to these various error sources are compared for circular orbits in the altitude regime 300–800 km during solar minimum F10.7=72.5 $\left({F}_{10.7}=72.5\right)$. EDR and POD accelerometry have comparable performances for high drag, low POD noise environments, whereas the latter performs considerably better in low drag <10−6m/s2 $\left(< 1{0}^{-6}\ \mathrm{m}/{\mathrm{s}}^{\mathrm{2}}\right)$, high POD noise (>25 ${ >} 25$ cm) environments, with densities retrieved at higher cadences for the orbital regimes considered in this work during solar minimum. Plain Language Summary: Low Earth orbit (LEO) Satellites orbit the Earth within its tenuous upper atmosphere. The uncertainties in the modeling of the atmospheric density lead to considerable errors in the prediction of satellite orbits that can have drastic consequences in the increasingly overcrowded LEO regime. Therefore, real‐time estimates of the upper atmospheric density are very beneficial in improving the predictive capability of atmospheric models. This research focuses on using tracking data from satellites equipped with GNSS receivers to estimate atmospheric densities in LEO. Specifically, the study analyzes two methods that derive density estimates from precision orbit determination (POD) products. The research examines the impact of different error sources on the accuracy of density estimates during quiescent conditions in solar minimum. Strategies to mitigate these errors are also suggested. Overall, this research contributes to understanding the effectiveness of different methods for deriving atmospheric densities from POD products obtained from GNSS‐equipped satellites in LEO for the nominal space weather conditions considered here. It highlights the importance of considering various error sources and provides the reader with the trade‐offs in selecting a method to estimate atmospheric densities from tracking data in different operational conditions for circular satellite orbits during solar minimum. Key Points: Precision orbit determination (POD) accelerometry and energy dissipation rate (EDR) are evaluated for density retrieval in 300–800 km at solar minimum, assessing performance, and error sensitivityPOD accelerometry enables better handling of dynamical errors and excels in low‐drag, high‐noise environmentsEDR proves to be a viable option in high‐drag environments and low POD uncertainties [ABSTRACT FROM AUTHOR]

Increasing carbon dioxide concentrations in the mesosphere and lower thermosphere are increasing radiative cooling in the upper atmosphere, leading to thermospheric contraction and decreased neutral mass densities at fixed altitudes. Previous studies of the historic neutral density trend have shown a dependence upon solar activity, with larger F10.7 values resulting in lower neutral density reductions. To investigate the impact on the future thermosphere, the Whole Atmosphere Community Climate Model with ionosphere and thermosphere extension has been used to simulate the thermosphere under increasing carbon dioxide concentrations and varying solar activity conditions. These neutral density reductions have then been mapped onto the Shared Socioeconomic Pathways published by the Intergovernmental Panel on Climate Change. The neutral density reductions can also be used as a scaling factor, allowing commonly used empirical models to account for CO2 trends. Under the "best case" SSP1‐2.6 scenario, neutral densities reductions at 400 km altitude peak (when CO2 = 474 ppm) at a reduction of 13%–30% (under high and low solar activity respectively) compared to the year 2000. Higher CO2 concentrations lead to greater density reductions, with the largest modeled concentration of 890 ppm resulting in a 50%–77% reduction at 400 km, under high and low solar activity respectively. Plain Language Summary: Carbon dioxide (CO2) concentrations are increasing throughout the atmosphere, not just at ground level. While this results in global warming in the lower atmosphere, the much less dense upper atmosphere does not trap the radiated heat, resulting in cooling of the upper atmosphere. As the upper atmosphere cools, it contracts, reducing the atmospheric density at a fixed altitude. Satellites traveling in low Earth orbit, such as the International Space Station at 400 km altitude, experience atmospheric drag, slowly reducing their altitude until they "re‐enter" and burn up in the lower, denser atmosphere. Reducing neutral densities will increase satellite orbital lifetimes as they experience less drag. The upper atmosphere has been simulated under increasing CO2 concentrations and solar activity conditions. This has also been linked to potential future CO2 concentration scenarios. Scaling factors have been created allowing simpler, faster models to account for CO2 density reductions. Under a best‐case scenario (SSP1‐2.6) where CO2 concentrations peak in around the year 2065 and then decline, densities at 400 km are 13%–30% lower compared to the year 2000 at the CO2 peak concentration, and then recover as CO2 reduces. However, densities continue to reduce if CO2 concentrations keep rising. Key Points: Whole Atmosphere Community Climate Model with ionosphere and thermosphere extension has been used to model future thermospheric density reductions under increasing carbon dioxide concentrations and solar activityThe reductions in density have been mapped onto the Shared Socioeconomic Pathways to show future scenarios while accounting for solar cyclesDensities at 400 km are 13%–30% lower under high and low solar activity respectively in the SSP1‐2.6 scenario when CO2 peaks at 474 ppm [ABSTRACT FROM AUTHOR]

Abstract Atmospheric neutral density is a crucial component to accurately predict and track the motion of satellites. During periods of elevated solar and geomagnetic activity atmospheric neutral density becomes highly variable and dynamic. This variability and enhanced dynamics make it difficult to accurately model neutral density leading to increased errors which propagate from neutral density models through to orbit propagation models. In this paper we investigate the dynamics of neutral density during geomagnetic storms. We use a combination of solar and geomagnetic variables to develop three Random Forest machine learning models of neutral density. These models are based on (a) slow solar indices, (b) high cadence solar irradiance, and (c) combined high‐cadence solar irradiance and geomagnetic indices. Each model is validated using an out‐of‐sample data set using analysis of residuals and typical metrics. During quiet‐times, all three models perform well; however, during geomagnetic storms, the combined high cadence solar iradiance/geomagnetic model performs significantly better than the models based solely on solar activity. The combined model capturing an additional 10% in the variability of density and having an error up to six times smaller during geomagnetic storms then the solar models. Overall, this work demonstrates the importance of including geomagnetic activity in the modeling of atmospheric density and serves as a proof of concept for using machine learning algorithms to model, and in the future forecast atmospheric density for operational use.

The mechanism of electrical interaction between subsystems in the Earth–atmosphere–ionosphere–magnetosphere system is currently the least studied and substantiated subject. Moreover, some experts doubt its existence. This study is devoted to investigating the mechanisms of generation and propagation of electric fields that vary in time under the influence of transient high-energy sources of various physical nature and atmospheric turbulence enhanced by these sources, which is an urgent problem. Four options of penetration of electric fields from the atmospheric surface layer into the ionosphere have been proposed. Electrical parameters that depend on disturbances in the electric charge density and the characteristics of atmospheric turbulence have been estimated and numerically calculated for a number of high-energy sources. It is shown that the disturbances arising in the atmospheric surface layer are capable of penetrating into the ionosphere and even into the magnetosphere. [ABSTRACT FROM AUTHOR]

As part of the Pandonia Global Network (PGN), Pandora spectrometers are widely deployed around the world. These ground-based, remote-sensing instruments are federated such that they employ a common algorithm and data protocol for reporting on trace gas column densities and lower atmospheric profiles using two modes based on direct-sun and sky-scan observations. To aid users in the analysis of Pandora observations, the PGN standard quality assurance procedure assigns flags to the data indicating high, medium, and low quality. This work assesses the suitability of these data quality flags for filtering data in the scientific analysis of nitrogen dioxide (NO2) and formaldehyde (HCHO), two critical precursors controlling tropospheric ozone production. Pandora data flagged as high quality assures scientifically valid data and is often more abundant for direct-sun NO2 columns. For direct-sun HCHO and sky-scan observations of both molecules, large amounts of data flagged as low quality also appear to be valid. Upon closer inspection of the data, independent uncertainty is shown to be a better indicator of data quality than the standard quality flags. After applying an independent uncertainty filter, Pandora data flagged as medium or low quality in both modes can be demonstrated to be scientifically useful. Demonstrating the utility of this filtering method is enabled by correlating contemporaneous but independent direct-sun and sky-scan observations. When evaluated across 15 Pandora sites in North America, this new filtering method increased the availability of scientifically useful data by as much as 90 % above that tagged as high quality. A method is also developed for combining the direct-sun and sky-scan observations into a single dataset by accounting for biases between the two observing modes and differences in measurement integration times. This combined data provides a more continuous record useful for interpreting Pandora observations against other independent variables such as hourly observations of surface ozone. When Pandora HCHO columns are correlated with surface ozone measurements, data filtered by independent uncertainty exhibits similarly strong and more robust relationships than high-quality data alone. These results suggest that Pandora data users should carefully assess data across all quality flags and consider their potential for useful application to scientific analysis. The present study provides a method for maximizing use of Pandora data with expectation of more robust satellite validation and comparisons with ground-based observations in support of air quality studies. [ABSTRACT FROM AUTHOR]

• Size-resolved Effective density of submicron atmospheric particles in Shenzhen were measured online using DMA-CPMA-CPC combined system. • Bimodal distribution feature of particle effective density was identified, including a main density mode and a sub density mode, by bimodal Gaussian fitting. • Particle effective density exhibited a high occurrence frequency of bimodal distribution, and two density modes exhibited opposite size distribution trends. • Effective density variation was highly correlated with the proportion of OA, sulfates and BC. Effective density (ρ eff) is one of the most important physical properties of atmospheric particles, providing important references in exploring the emissions and aging processes of fresh particles. In this study, a combined system of differential mobility analyzer, centrifugal particle mass analyzer, and condensation particle counter was used to periodically measure the ρ eff of atmospheric particles in Shenzhen from Oct. 2021 to Jan. 2022. Results showed that the ρ eff of particles with various size presented a bimodal distribution, which could be divided into main density (ρ m , main peak, corresponding to relatively dense particles after aging) and sub density (ρ s , sub peak, corresponding to fresh particles). The occurrence frequencies of ρ s of particles with diameters of 50 and 80 nm were less than 20%, but were as high as about 40% of that with diameters from 120 to 350 nm. The ρ m showed increasing trend with the size of particles, while ρ s decreased as the increasing of the size of particles. The ρ eff on pollution day varied significantly with chemical compositions. The increasing of the proportion of sulfate could promote the increasing of ρ eff , while black carbon and organic matter caused opposite effects, which may be related to various factors, including the difference of the material density and morphology of various chemical components. The ρ eff of 50, 80 and 120 nm particles decreased considerably during the new particle formation event, indicating that organic condensation was an important contributor to new particle growth. [ABSTRACT FROM AUTHOR]

Since the late 1950s, when the first artificial satellite was launched, the number of Resident Space Objects has steadily increased. It is estimated that around one million objects larger than one cm are currently orbiting the Earth, with only thirty thousand larger than ten cm being tracked. To avert a chain reaction of collisions, known as Kessler Syndrome, it is essential to accurately track and predict debris and satellites' orbits. Current approximate physics-based methods have errors in the order of kilometers for seven-day predictions, which is insufficient when considering space debris, typically with less than one meter. This failure is usually due to uncertainty around the state of the space object at the beginning of the trajectory, forecasting errors in environmental conditions such as atmospheric drag, and unknown characteristics such as the mass or geometry of the space object. Operators can enhance Orbit Prediction accuracy by deriving unmeasured objects' characteristics and improving non-conservative forces' effects by leveraging data-driven techniques, such as Machine Learning. In this survey, we provide an overview of the work in applying Machine Learning for Orbit Determination, Orbit Prediction, and atmospheric density modeling. [Display omitted] • Survey the introduction of new statistical techniques for Orbital Estimation. • Overview of deep learning techniques to improve empirical atmospheric density models. • Systematically study trends in Orbital Estimation using ML-based enhancements. • Define potential applications of Machine Learning approaches to Orbit Determination. [ABSTRACT FROM AUTHOR]

The features of upper atmospheric midnight density maximum (MDM) around low geographic latitudes are studied based on neutral mass densities data at altitudes 360–480 km, derived from the accelerometer measurements aboard on the three polar orbiting satellites CHAMP (CHAllenging Minisatellite Payload), GRACE-A (Gravity Recovery and Climate Experiment-A), and SWARM-C (The Earth's Magnetic Field and Environment Explorers-C). The MDM appears during the local times from 23:00 to 02:00 LT (Local Time), whose peak locates at the low latitudes within 15 ∘ and two valleys locate at the middle latitudes between 35 ∘ and 45 ∘ on both hemispheres separately. The structure of MDM drifts toward the southern hemisphere overall. The MDM's amplitude decreases with increases in altitude and solar radiation level. The seasonal effect weakens the MDM's amplitudes around the summer and winter solstices, while the amplitudes around the spring and autumn equinoxes are extremely significant due to the slight seasonal difference between both hemispheres. Three atmospheric density models DTM2000 (Drag Temperature Model 2000), NRLMSISE00 (US Naval Research Laboratory Mass Spectrometer and Incoherent Scatter Radar Extended atmosphere model), and JB2008 (Jacchia-Bowman 2008 model) are used to simulate the MDM along these three satellites' orbits, and compared with the observations. It is found that the JB2008 model is failed to describe the MDM, and the other two models underestimate the MDM's amplitudes at altitudes 360 km and 480 km: the simulated amplitudes by the DTM2000 model are 46% and 53% of the observed amplitudes, respectively, and only 33% and 26% for the NRLMSISE00 model. These three models are also failed to depict the MDM's variation with altitude, solar radiation level, and seasonal effects. In order to correct the model prediction, a 6th-order Legendre polynomial of geographic latitude, coupled with arguments of local time and altitude, is designed to fit the MDM signals from the three satellites' observations. In terms of amplitude and phase of the MDM, the fitting results agree with the observations very well, and the correlation coefficient is 0.923. It indicates that this empirical polynomial could be helpful to the density model correction and high accuracy prediction of spacecrafts in low Earth orbits. [ABSTRACT FROM AUTHOR]

Exoplanet atmospheres are expected to vary significantly in thickness and chemical composition, leading to a continuum of differences in surface pressure and atmospheric density. This variability is exemplified within our Solar System, where the four rocky planets exhibit surface pressures ranging from 1 nPa on Mercury to 9.2 MPa on Venus. The direct effects and potential challenges of atmospheric pressure and density on life have rarely been discussed. For instance, atmospheric density directly affects the possibility of active flight in organisms, a critical factor since without it, dispersing across extensive and inhospitable terrains becomes a major limitation for the expansion of complex life. In this paper, we propose the existence of a critical atmospheric density threshold below which active flight is unfeasible, significantly impacting biosphere development. To qualitatively assess this threshold and differentiate it from energy availability constraints, we analyze the limits of active flight on Earth, using the common fruit fly, Drosophila melanogaster, as a model organism. We subjected Drosophila melanogaster to various atmospheric density scenarios and reviewed previous data on flight limitations. Our observations show that flies in an N2-enriched environment recover active flying abilities more efficiently than those in a helium-enriched environment, highlighting behavioral differences attributable to atmospheric density vs. oxygen deprivation. [ABSTRACT FROM AUTHOR]

This study determined the electron temperature and density in atmospheric pressure argon plasma using optical emission spectroscopy. The analysis combined continuum and line spectral data. Visible bremsstrahlung inversion was used to derive a partial electron energy probability function (EEPF) from the continuum spectrum. Subsequently, electron temperature was estimated assuming a two-temperature distribution based on the derived EEPF. Electron density was obtained by fitting a collisional-radiative (CR) model to the line spectrum, incorporating the obtained EEPF instead of assuming a Druyvesteynian EEPF. Comparative analysis revealed that the electron densities determined using the approach were approximately one order of magnitude lower than those derived from the CR model with the Druyvesteynian EEPF. However, they exhibited strong agreement with the results obtained by the CR model using a two-temperature distribution. This approach demonstrated favorable performance in reproducing both continuum and line spectra, revealing its high reliability and accuracy for atmospheric pressure argon plasma diagnosis. [ABSTRACT FROM AUTHOR]

The standard recommended atmospheric gravity correction is based on the International Association of Geodesy (IAG) approach. This correction introduced into the results of gravimetric measurements reduces, in a simplified way, the influence of the actual atmospheric masses and the atmospheric masses contained inside a reference ellipsoid from the determined gravity anomalies or disturbances. Model of the actual atmosphere used in the IAG approach does not take into account topography as the lower boundary of the atmosphere, assuming that the atmosphere consists of spherical, constant density layers. In this study, we determined and analysed the components of atmospheric gravity correction for the area of Poland and its surroundings, considering topography as the lower limit of the atmosphere. In the calculations, we used algorithms typical for determining the topographic gravity reduction, assuming a model of atmospheric density based on the United States Standard Atmosphere 1976 model. The topography-bounded gravity atmospheric correction values determined were within the limits of 0.748–0.886 mGal and were different from standard, approximate atmospheric correction values in the range of 0.011 mGal for points at the sea level up to 0.105 mGal for points located at an altitude of approximately 2600 m. [ABSTRACT FROM AUTHOR]

The stellar occultation technique is capable of atmospheric trace gas detection using the molecule absorption characteristics of the stellar spectra. In this paper, the non-iterative and iterative retrieval methods for oxygen and air density detection by stellar occultation are investigated. For the single-band average transmission data in the oxygen 761 nm A-band, an onion-peeling algorithm is used to calculate the effective optical depth of each atmospheric layer, and then the optical depth is used to retrieve the oxygen number density. The iteration method introduces atmospheric hydrostatic equilibrium and the ideal gas equation of state, and it achieves a more accurate retrieval of the air density under the condition of a priori temperature deviation. Finally, this paper analyzes the double solution problem in the iteration process and the ideas to improve the problem. This paper provides a theoretical basis for the development of a new type of atmospheric density detection method. [ABSTRACT FROM AUTHOR]

The thermospheric density and its variations are crucial to aerospace activities as well as space weather research and operation. However, due to the difficulties in observing the thermosphere, there has been a lack of effective descriptions for the general characteristics of thermospheric density. In this paper, the Two‐Line‐Element data sets (TLEs) from multi‐target low Earth orbit satellites are used to derive a proxy of the daily average atmospheric density in the thermospheric shell located in the vicinity of LEOs' orbital altitude. It captures the overall characteristics of the thermosphere and exhibits good correlations (∼0.9) with modeled and observed thermospheric density. By applying the spectral whitening method to this proxy, a new index JsT ${J}_{s}^{T}$ is derived to describe non‐periodic perturbation of the density where the specific satellite passed by. The fact that the JsT ${J}_{s}^{T}$ obtained from different satellites within the same thermospheric shell presents significant consistency to each other means that the new index is a good indicator for the overall feature of the variations of thermospheric density, and it is possible to define a unified regional index JrT ${J}_{r}^{T}$ to describe density disturbances for the thermospheric shell where these satellites fly through. Moreover, the JrT ${J}_{r}^{T}$ at different altitudes also present good consistency suggesting the possibility of defining a global index JpT ${J}_{p}^{T}$, capable of describing the density variation of the entire thermosphere. Plain Language Summary: Due to limited in situ observation, the thermospheric density is not easy to obtain. Herein, we have extracted the density information of the thermosphere based on the Two‐Line‐Element data sets and developed a new index using the spectral whitening method, which describes aperiodic disturbances of the density. The construction of this index series can address the limitations of existing quantitative or graded descriptions of space weather disturbances and the problem of mismatched or inconsistent parameters/indices. Ultimately, this will contribute to the monitoring and warning of space weather causal chains. Key Points: A proxy of daily average thermospheric mass density was extracted from Two‐Line‐Element data setsBy applying the spectral whitening method to this proxy, a new index is derived to describe non‐periodic perturbations in the thermosphereA unified regional index was defined to describe density disturbances for the thermospheric shell where these satellites fly through [ABSTRACT FROM AUTHOR]

This paper introduces an innovative approach for generating re-entry trajectories for a reusable winged spacecraft. This approach utilizes Fourier series parametrized control profiles. The Fourier coefficients are derived through a combination of the Improved Search Space Reduction (ISSR) technique and Sequential Quadratic Programming (SQP) optimization methods, which effectively limit the maximum heat rate experienced by the spacecraft. These re-entry trajectories and control profiles are then used to train artificial neural networks, enabling the controller to provide optimal control inputs based on the spacecraft's current altitude and velocity. To validate this methodology, Hardware-in-loop (HIL) simulations are conducted, integrating the designed neural network-based controller with a Texas Instruments TI Delfino TMSF28335 controller and a real-time simulator, the OPAL-RT OP4510. The results of the HIL simulation demonstrate that the generated re-entry trajectory accurately adheres to heat rate and terminal constraints. Additionally, the Fourier series parametrization of control profiles is applied to a high lift-to-drag ratio CAV-H vehicle, showcasing the method's versatility. Furthermore, resilience of proposed method to uncertainties in aerodynamic coefficients and atmospheric density is also demonstrated. The results show that the proposed method is generic and exhibits robustness to uncertainties. [ABSTRACT FROM AUTHOR]

Io, the closest of Jupiter's four Galilean moons, suffers from intense ion bombardment from Jupiter's magnetosphere. The constant atmospheric erosion by energetic ion precipitation, referred to atmospheric sputtering, serves as an important mechanism of Io's atmospheric escape. This study is devoted to a state‐of‐the‐art study of atmospheric sputtering at Io, with the aid of constantly accumulated understandings of Io's space environment and atmospheric photochemistry, as well as the updated laboratory measurements. A Monte Carlo model is constructed to track the energy degradation of incident S++ and O+ and atmospheric recoils from which the sputtering yields of different atmospheric species are determined. Our calculations suggest a total escape rate of 3 × 1029 atom s−1 on Io, and SO2 is the dominant sputtered species. Further investigations reveal that S++ is the most efficient species for atmospheric sputtering on Io, and sputtering yields increase substantially with increasing incident ion mass, energy, and incidence angle. The model sensitivity to different influence factors is also discussed, including scattering angle distribution, atmospheric column density, proton precipitation, inelastic process, and surface sputtering, of which the former two dominate. Plain Language Summary: As the closest Galilean moon of Jupiter, Io is strongly influenced by high energy ions from Jupiter's magnetosphere. The collisions between these high energy ions and background atmospheric particles can produce considerable high energy atmospheric recoils. A large portion of these particles are able to escape to space when their kinetic energies exceed local escape energy. Such a phenomenon is named atmospheric sputtering. In this study, we simulate this process on Io with the aid of parameters from laboratory measurements and a Monte Carlo model. Our calculations show that sputtering is the most important process driving atmospheric loss at Io. We also analyze the effects of various incident plasma populations and model setups on the atmospheric sputtering at Io. Key Points: Atmospheric sputtering is the most important mechanism driving atmosphere escape at IoOur calculations suggest a total escape rate of 3 × 1029 atom s−1 on IoSputtering yields vary substantially with incident plasma and atmospheric conditions, yet are insensitive to proton precipitation and inelastic process [ABSTRACT FROM AUTHOR]

Vertical transport of heat and atmospheric constituents by gravity waves plays a crucial role in shaping the thermal and constituent structure of the middle atmosphere. We show that atmospheric mixing by non‐breaking waves can be described as a diffusion process where the potential temperature (KH) and constituent (KWave) diffusivities depend on the compressibility of the wave fluctuations and the vertical Stokes drift imparted to the atmosphere by the wave spectrum. KH and KWave are typically much larger than the eddy diffusivity (Kzz), arising from the turbulence generated by breaking waves, and can exceed several hundred m2s−1 in regions of strong wave dissipation. We also show that the total diffusion of heat and constituents caused by waves, turbulence, and the thermal motion of molecules, is enhanced in the presence of non‐breaking waves by a factor that is proportional to the variance of the wave‐driven lapse rate fluctuations. Diffusion enhancements of both heat and constituents of 50% or more can be experienced in regions of low atmospheric stability, where the lapse rate fluctuations are large. These important transport effects are not currently included in most global chemistry‐climate models, which typically only consider the eddy diffusion that is induced when the unresolved, but parameterized waves, experience dissipation. We show that the theoretical results compare favorably with observations of the mesopause region at midlatitudes and describe how the theory may be used to more fully account for the unresolved wave transport in global models. Plain Language Summary: Winds blowing over topography and weather systems in the lower atmosphere can generate waves that propagate into the upper atmosphere to the edge of space, where their amplitudes become very large in response to decreasing atmospheric density. These waves drive the global circulation of the middle and upper atmosphere and can even affect satellite orbits and space weather. They also play very important roles in transporting heat and constituents vertically by mixing the atmosphere, which causes diffusion, and by inducing a net vertical motion, called Stokes drift. Unfortunately, global chemistry‐climate models cannot resolve the important small‐scale waves, which make the largest contributions to wave transport. Existing models account for wave transport by simply calculating the eddy mixing by turbulence that arises when waves break. We develop a general theory to describe wave‐driven diffusion and advection of heat and constituents in the atmosphere and show how the theory can be used to estimate the transport caused by unresolved, non‐breaking waves in atmospheric models. These results are important because they demonstrate the significance of wave transport, apart from simple eddy mixing, and provide a method for incorporating this crucial, but currently missing process, in future global chemistry‐climate models. Key Points: Non‐breaking gravity waves induce strong vertical transport that depends on compressibility of wave fluctuations and wave‐driven Stokes driftTheory compares favorably with observations of the mesopause region at midlatitudesResults can be used to parameterize transport of heat & constituents induced by unresolved waves in global chemistry‐climate models [ABSTRACT FROM AUTHOR]

A remarkable large-amplitude density modulation has been observed in ozone-mixed oxygen gas at atmospheric density and temperature conditions following irradiation with a nanosecond pulse of ultraviolet laser radiation. This paper outlines the experimental findings and describes a hydrodynamic simulation that reproduces several quantitative aspects of this phenomenon. It is important to note that these density waves are not simple sound waves; instead, they are combined with another type of density modulation wave. These density modulation wave profiles are expected to have applications for new optical components using a gas medium. [ABSTRACT FROM AUTHOR]

• The precise orbit data of the re-entry objects SZ-10 MODULE and TIANGONG 1 are adopted to retrieve the thermospheric mass densities below 200 km altitude. • The energy balance method is introduced and improved to the retrieval of the thermospheric mass densities below 200 km altitude. • The retrieved densities and their ratios with the NRLMSISE-00 empirical model are analyzed in terms of latitude and local time. Atmospheric mass densities in the lower thermosphere below 200 km have not been adequately determined, but they are crucial for re-entry prediction of space objects. In this paper, based on precise orbit data of the re-entry objects SZ-10 MODULE and TIANGONG 1 (COSPAR identifiers 2013-029H and 2011-053A, respectively; NORAD catalog numbers 39193 and 37820, respectively), the semi-major axis decay numerical method and the improved energy balance method are adopted to retrieve thermospheric mass densities below 200 km altitude, and a total of 7044 and 4698 points of valid densities data with one-minute temporal resolution are obtained, respectively. Then the retrieved densities after preprocessing are compared with the NRLMSISE-00 empirical model of the atmosphere. It shows that there is an excellent consistency between these two methods with the Pearson correlation coefficients around 1.00, the retrieved densities of which are also in good agreement with the model with the Pearson correlation coefficients above 0.97 (their systematic biases are about 1.1 % and 4.5 % with standard deviations of about 14 % and 20 % for these two objects respectively), but the retrieved densities of the semi-major axis decay numerical method have a smaller systematic bias from the model than the results of the improved energy balance method which is computationally more efficient. In addition, the corresponding retrieved densities and their ratios to the model are further analyzed in terms of latitude and local solar time, and the retrieved densities of these two methods are also in good consistency within about 97 %. The maximum mean deviations from the model in both dimensions reach about 12 %. It reveals the variations of the thermospheric mass densities below 200 km altitude with latitude and local solar time due to solar activity. Additionally, it also indicates that the NRLMSISE-00 model underestimates the thermospheric densities at high solar activity and overestimates the densities at low solar activity, as compared to the retrieved densities that are regarded as true values. [ABSTRACT FROM AUTHOR]

In 1995, the Galileo spacecraft traversed the wake of Io at ∼900 km altitude. The instruments onboard detected intense bi‐directional field‐aligned electron beams (∼140 eV–150 keV), embedded in a dense, cold and slow plasma wake (Nel ∼ 35,000 cm−3, Ti < 10 eV, V < 3 km/s). Similar electron beams were also detected along subsequent Galileo flybys. Using numerical simulations, we show that these electron beams are responsible for the formation of Io's dense plasma wake. We prescribe the composition of Io's atmosphere in S, O, SO and SO2, compute the atmospheric ionization by the beams with a parameterization adapted from study of auroral electrons at Earth, the plasma flow into Io's atmosphere with a Magneto‐Hydro‐Dynamic code, and the ion composition and temperature with a multi‐species physical chemistry code. Results reveal contrasting chemistries between the upstream and wake regions, leading to different ion compositions. The upstream chemistry is driven by the torus thermal electrons at 5 eV with SO2+ becoming the dominant ion because of electron‐impact ionization of the SO2 atmosphere. The wake chemistry is driven by the high‐energy electrons in the beams with S+ and SO+ becoming the dominant ions produced by dissociative‐ionization of SO2. We show that the wake ion composition is highly sensitive to the atmospheric composition. Juno, in its extended mission, will traverse Io's wake and determine its ion composition, which, compared with our numerical simulations will enable us to infer the detailed composition of the atmosphere. Plain Language Summary: Io, the inner‐most Galilean moon of Jupiter, is the most active volcanic body of the solar system. It has a tenuous atmosphere ultimately supplied by volcanic activity. The atmosphere is mainly composed of sulfur dioxide, oxygen, sulfur and sulfur monoxide, but its detailed composition, density and spatial distribution are still surprisingly poorly known. Between 1995 and 2001, the Galileo spacecraft made five close flybys of Io. The onboard instruments detected intense high‐energy electrons moving along Jupiter's magnetic field lines embedded in a remarkably dense ion wake (∼10 times denser than the surrounding plasma). Identifying the processes that generate this dense wake remains an outstanding issue. We utilize numerical simulations to demonstrate that the production of the dense ion wake is attributed to efficient ionization of Io's atmosphere by the electron beams. Our simulations reveal that the ion composition of the wake is highly sensitive to the atmospheric composition. The Juno spacecraft, currently in orbit around Jupiter, will conduct several flybys in Io's wake in 2023 and 2024 and determine its ion composition. Similar electron beams are likely present near other moons of Jupiter. Such beams have already been detected during a single flyby of Europa by the Juno probe. The Jupiter Icy Moon Explorer spacecraft is presently en route to Ganymede and Callisto, while the future Europa Clipper mission is scheduled to be launched to Europa in 2024. These missions will have the capacity to detect the presence of electron beams and plasma wakes similar to those observed at Io. Our numerical model serves as an effective tool for inferring the atmospheric composition and density of these moons as it predicts the ion composition and density of the wake based on the energy of the electron beams. Key Points: The Galileo spacecraft detected a dense and cold plasma wake downstream of Io and intense field‐aligned high‐energy electron beamsUsing numerical simulations, we show that this dense plasma wake is produced by the electron beams ionization of Io's atmosphereThe ion composition and density in the wake strongly depend on Io's atmospheric density and its neutral composition [ABSTRACT FROM AUTHOR]

Currently, the exploration of the planet Venus is a very relevant and developing direction in space science. The development of rocket and space technologies has expanded the boundaries of accessibility of spacecraft to objects in the Solar System, allow for entire interplanetary expeditions, including flights to terrestrial planets, giant planets, and the outskirts of the Solar System. Currently, a program of planetary exploration for the next decades is being formed. Studying the history of expeditions to Venus and Mars clarifies the need to develop and improve methods for studying the atmosphere of the nearest planets to Earth, in particular, Venus, using vailable technical means, making them as efficient as possible. The exploration of Venus is proposed to be carried out using a technical means– a multirotor aircraft. This object is allocated as a system, and its role in the composition of the supersystem is also defined and described. The paper identifies scenarios for the functioning of the flying apparatus are highlighted, the tasks of its subsystems are described, as well as their interaction with each other. The main external factors affecting the work of the subsystems of the multirotor aircraft are presented. A functional scheme of the system is developed, as well as the main indicators used to assess the effectiveness of achieving the target task. This work is a preliminary stage before building a mathematical model.

The ESA mission EnVision will address its main scientific questions through a detailed mapping of the surface and interior properties of Venus. A precise reconstruction of the spacecraft trajectory is a key requirement for the EnVision scientific investigations, including radio science. To precisely constrain the orbit evolution, refined models of the dynamical forces are included in the Precise Orbit Determination (POD) process. We developed a methodology based on a batch-sequential filter that enables a joint estimation of Venus gravity and atmospheric density. Our approach yields an accurate compensation of atmospheric mismodeling, simulated through semi-empirical predictions of the atmospheric density provided by general circulation models (GCM), e.g. , Venus Climate Database (VCD). Numerical simulations of the EnVision radio science investigation were carried out by using a perturbative analysis of the dynamical forces, which accounts for atmospheric density errors ≥ 200%. By adjusting a set of atmospheric scale factors, our proposed strategy enables an estimation of the atmospheric density at the spacecraft altitudes with an accuracy of 25%. The improved dynamical model yields accuracies in the orbit reconstruction of 1–2 m, 30–40 m and 20–30 m in the radial, transverse and normal directions. • We present an enhanced approach for the precise orbit determination of the ESA EnVision mission. • Our method enables a joint determination of Venus' gravity and atmospheric density. • We discuss a thorough analysis of uncompensated atmospheric drag mismodeling. • The retrieved atmospheric scale factors are used to correct Venus' atmospheric model predictions. [ABSTRACT FROM AUTHOR]

Based on the TraPPE force field, previously unknown values of the parameters of the intermolecular interaction potential of trans-decalin were determined. Parametrization was carried out using experimental data on saturated vapor pressure and density at atmospheric pressure. The found parameters make it possible to adequately describe the boiling and condensation lines of trans-decalin and also predict the critical values of pressure, density, and temperature with satisfactory accuracy. Calculations of vapor-liquid phase equilibrium conditions for a binary CO2—trans-decalin mixture in supercritical conditions for CO2 were carried out. When quantitatively comparing the calculated values with experimental data, an underestimation of pressure at a temperature of 345.4 K by 30% is observed, which decreases to 5% for temperatures up to 525 K. [ABSTRACT FROM AUTHOR]

In recent years, atmospheric-pressure plasma jets have emerged as valuable tools in many application areas, including material modification, environmental remediation and biomedicine. Understanding the discharge characteristics of these plasma jets under various operating conditions is crucial for optimizing process outcomes. This paper presents a two-dimensional fluid model for numerical simulation to study the variation in electron density within an atmospheric-pressure helium plasma jet under different operating conditions. The investigated parameters include helium gas flow rate, voltage amplitude, needle-to-ring discharge gap, and relative permittivity of the dielectric tube. The results reveal that the peak electric field and electron density initially occur at the wall of the dielectric tube and subsequently shift towards the head of the propagating jet. Gas flow rate has minimal impact on the electron density throughout the plasma jet, whereas increasing the needle-to-ring discharge gap significantly decreases the average electron density within the jet. In addition, an increase in the voltage amplitude and the relative permittivity of the dielectric tube enhances the electric field within the discharge space, thereby increasing the electron density in the plasma jet. These findings underscore the importance of understanding the correlation between electron density and operating conditions to precisely control plasma jets and enhance material treatment effectiveness for specific applications. [ABSTRACT FROM AUTHOR]

Solar radiation, and specifically solar spectral irradiance in EUV, influence the Earth's atmosphere. It affects the Ionosphere-Thermosphere-Mesosphere (ITM) system. Variations in atmospheric density depend on solar irradiance, solar wind and geomagnetic storms, generating heat in the neutral atmosphere. Thus, satellites flying at high altitude regions experience drag force increase. These effects reduce the life of satellites and introduce significant errors in orbital tracking. Reliable measurements of solar spectral irradiance (EUV) over long time scales are necessary to understand its effect on the upper atmosphere. Specifically, to improve the neutral density predictions in the thermosphere, avoiding satellite loss due to the drag and avoiding collisions. [ABSTRACT FROM AUTHOR]

The most common model of linear economy is currently unsustainable, from the economic, energy and ecological aspects. The enormous increase in human needs for various products and energy has led to a reduction in raw material reserves, on the one hand, and the accumulation of waste, on the other. Therefore, it is necessary to widely adopt the circular economy model, where waste is treated as a raw material, with the idea of achieving zero waste production without use of virgin raw materials. In that sense, in this work food and agricultural waste was used to obtain liquid and solid biofuels. Used cooking oil was used as a raw material in the production of biodiesel, while the waste shell of a hen's egg served as the source of a catalyst for the reaction. Glycerine, as a side product of the chemical reaction, was mixed with agricultural and woody biomass in the production of enriched pellets. The fuels obtained in this way were thermodynamically characterized. For biodiesel and glycerine, the density and viscosity at atmospheric pressure and temperatures were measured, while for the mixtures of crude glycerine and biomass, the calorific value was determined. The obtained products show promising characteristics as potential energy source. [ABSTRACT FROM AUTHOR]

The entry of a meteoroid into the atmosphere and interaction between them are considered. The motion, ablation, and energy deposition of a meteoroid or its fragments moving as a single body are modeled by numerical solution of the meteor physics equations. The main parameter in these equations is the ablation parameter, which is equal to the ratio of the heat transfer coefficient to the effective enthalpy of mass loss. Therefore, the setting of the heat transfer coefficient is of crucial importance in modeling the interaction of a meteoroid with the atmosphere. For the heat transfer coefficient, a correlation is used, which depends on the velocity of the body, its radius, and the atmospheric density. This correlation is an approximation of the published numerical calculations; the convective heat flux is also taken into account. The results of radiative heating simulations in the meteor range of parameters involve some uncertainty since many factors are not taken into account in the computations or are not known. Therefore, an uncertainty parameter is introduced in the formula for the heat transfer coefficient. This parameter is varied to examine the influence of the inaccuracy of setting the ablation parameter on the meteoroid velocity, mass loss, trajectory, and energy deposition along the trajectory. [ABSTRACT FROM AUTHOR]

This research proposes a new strategy for Mars orbit injection, based on aerocapture and low-thrust nonlinear orbit control. The range of periapse altitudes that allow aerocapture is identified as a function of the hyperbolic excess velocity at Mars arrival, with reference to a large variety of atmospheric density profiles and different ballistic coefficients. This analysis proves that a safe periares altitudinal range leading to aerocapture in all atmospheric conditions does not exist. Three different correction maneuvers, aimed at avoiding both impact and escape, are identified. After the atmospheric arc, the spacecraft orbit exhibits large dispersions in terms of orbit elements. Therefore, the identification of an effective autonomous guidance strategy, capable of driving the spacecraft toward the desired operational orbit, is mandatory. To do this, low-thrust nonlinear orbit control is proposed as an effective option. A feedback law for the low-thrust direction and magnitude, with saturation of the thrust magnitude, is defined, and is proven to enjoy global stability properties. As a result, the spacecraft travels toward the operational orbit of interest, i.e. either (a) an areostationary orbit, (b) a quasi-synchronous inclined orbit, or (c) a low-altitude, sunsynchronous orbit. Monte Carlo simulations, with stochastic density profiles and uncertain initial conditions, point out that the strategy at hand is successful and allows reducing the overall propellant budget in comparison to direct orbit injection based on chemical propulsion. Moreover, the overall time of flight typically ranges from 45 to 140 days, and therefore it is much shorter than that required with the use of aerobraking. As a last advantage, low-thrust nonlinear orbit control allows achievement of a variety of operational orbits, with great accuracy. • Aerocapture at Mars is investigated, either without or with correction maneuvers. • Capture corridors are identified. • Several correction maneuvers are defined, aimed at avoiding escape or impact. • Low-thrust nonlinear orbit control is used for precise orbit injection. • aerocapture and low-thrust orbit control is successfully tested for 3 final orbits. [ABSTRACT FROM AUTHOR]

The radio occultation method, one of the methods used to provide planetary atmospheric profiles with high vertical resolution, was applied to China's first Mars mission, Tianwen-1. We carried out observations based on the Chinese Deep Space Network, and one-way, two-way, and three-way modes were used for Doppler observations from the Tianwen-1 spacecraft. We successfully obtained effective observations from Tianwen-1 on 22 and 25 March 2022. An inversion system developed for Tianwen-1 radio occultation observations enabled the derivation of neutral atmospheric density, pressure, temperature, and electron density profiles of Mars. Utilizing one-way tracking data, Martian ionospheric electron density profiles were retrieved at latitudes between 68.7 and 70.7 degrees (N). However, the presence of strong random walk noise in one-way tracking data led to poor inversion results. Meanwhile, Martian ionospheric electron density and neutral atmosphere profiles were extracted from two-way and three-way tracking data at latitudes between 55.1 and 57.0 degrees (S) on 22 March and at latitudes between 62.8 and 63.4 degrees (S) on 25 March. Importantly, our inversion results from Tianwen-1 maintained consistency with results from the Mars Express and the Chapman theory (mainly in the M2 layer). Through two days' observation experiments, we established and verified the occultation solution system and prepared for the follow-up occultation plans. [ABSTRACT FROM AUTHOR]

The text discusses Peter Schultz, the recipient of the 2004 Barringer Medal, highlighting his contributions to impact cratering and planetary geology. Schultz's career, from his early teaching days to his groundbreaking research on impact-generated magnetic fields and atmospheric effects on ejecta emplacement, is detailed. His innovative approaches, experiments, and observations have significantly advanced our understanding of oblique impacts and cratering processes. Schultz's numerous awards, community involvement, and dedication to education further underscore his impact on the scientific community and society at large. [Extracted from the article]

Accurate prediction of the thermospheric density field has recently been gaining a lot of attention, due to an outstanding increase in space operations in Low-Earth Orbit, in the context of the NewSpace. In order to model such high-dimensional, non-Gaussian systems, Reduced-Order Models (ROMs) have been developed against existing physics-based density models. In general, the data-driven reconstruction of dynamical systems usually consists of two steps of compression and prediction. In this paper, we focus on the compression step and assess state-of-the-art order reduction methodologies such as autoencoders, linear, and nonlinear Principal Component Analysis (PCA). We show that Kernel-based PCA, a nonlinear generalization of PCA, can perform better than Neural Networks in representing the model in low-dimensional space in terms of accuracy, computational time, and energy consumption for both the Lorenz system, a chaotic dynamical system developed in the context of atmospheric modeling, and the thermospheric density. [ABSTRACT FROM AUTHOR]

Atmospheric drag is an important influencing factor in precise orbit determination and the prediction of low-orbit space debris. It has received widespread attention. Currently, calculating atmospheric drag mainly relies on different atmospheric density models. This experiment was designed to explore the impact of different atmospheric density models on the orbit prediction of space debris. In the experiment, satellite laser ranging data published by the ILRS (International Laser Ranging Service) were used as the basis for the precise orbit determination for space debris. The prediction error of space debris orbits at different orbital heights using different atmospheric density models was used as a criterion to evaluate the impact of atmospheric density models on the determination of space-target orbits. Eight atmospheric density models, DTM78, DTM94, DTM2000, J71, RJ71, JB2006, MSIS86, and NRLMSISE00, were compared in the experiment. The experimental results indicated that the DTM2000 atmospheric density model is best for determining and predicting the orbits of LEO (low-Earth-orbit) targets. [ABSTRACT FROM AUTHOR]

Relativistic Runaway Electrons Avalanches (RREAs) development depends on the applied electric field and the environment's air density. This dependency controls the RREA exponential growth length scale. The RREA development affects the bremsstrahlung excess occurring due to the passage of charged particles through the thundercloud's electric fields, the gamma‐ray glow. We used Monte Carlo simulations to develop an empirical model showing the RREA behavior in a realistic atmospheric density profile. The new formulation shows how the density variation modulates the electron population under electric field strengths near the RREA electric field threshold. The model limits the initial RREA altitude range as a function of the electric field strength. The new model is valid between ∼0.6 and ∼18 km, covering the relevant heights to investigate the generation of ground‐detected gamma‐ray glows. Plain Language Summary: Thunderclouds are energy sources for trespassing charged particles from cosmic rays. This extra energy gain may induce electron avalanches, known as Relativistic Runaway Electron Avalanches (RREAs), resulting in an enhanced gamma‐ray flux via bremsstrahlung, the gamma‐ray glow. Recent studies relate this enhancement to electric field strengths close to the RREA requirement. The atmospheric density variations affect avalanche development by modifying the RREA requirement, resulting in isolated avalanches by imposing limits to the avalanche's initial altitude. We show how RREAs develop in a realistic atmospheric density profile. We present a modification on the characteristic avalanche length under this condition. The initial avalanche altitude is crucial because it completely modifies the density profile trespassed by a downward electron shower. Finally, we discuss the consequences of isolated RREAs for high‐energy emissions and show that the electric field strength constrains the possible initial altitudes for the gamma‐ray glow. Key Points: A new empirical model quantifies how electron avalanches vanish because of atmospheric density variations with ∼10% accuracyThe model limits the initial altitude of electron avalanche development for electric field strengths near the avalanche thresholdWe narrow the possible gamma‐ray glow source height range with the new model which is valid through ∼0.6–18 km [ABSTRACT FROM AUTHOR]

Porous materials‐assisted atmospheric water harvesting (AWH) approaches are attractive for addressing the severe shortage of freshwater resources. Herein, ionothermal polymerization approach was employed to realize four porous organic polymers (FJU‐CTFs) with strong hydration stability and low skeleton density for atmospheric water harvesting. The materials exhibited ultra‐high water vapor adsorption capacity (1108 cm3 g−1), s‐type adsorption isotherms, and rapid filling of water vapor in the pores of the materials under low humidity conditions. It has the characteristics of atmospheric water harvesting from the air at lower humidity (30 %–40 %) and narrow temperature (30–35 °C). A total of 30 times of water adsorption‐desorption cycles showed the excellent working ability and hydrolytic stability of FJU‐CTFs, which provided new solutions for the application of porous materials in AWH and expanded new material types. [ABSTRACT FROM AUTHOR]

Cosmic-ray-induced particles at flight altitude present an increasing concern because of the development of aircraft with high maximum cruising altitude (higher than 40 000 ft) and because of the miniaturisation of and increase in the amount of embedded electronic systems. There are different codes used to estimate the radiation field through the atmosphere, using different approaches and Monte Carlo methods. This work aims to evaluate the influence on the neutron spectra at ground and flight altitude of the parameterizations employed to describe spallation reactions and the density profile of the atmosphere. The results show that different versions of Geant4 and the data driven models used significantly change the neutron fluence rate and the ambient dose equivalent rate. The results show that the different atmospheric density profiles considered do not significantly change the neutron spectra. In this work, we also present comparisons with onboard and ground level measurements. [ABSTRACT FROM AUTHOR]