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Recent studies of TWINS Lyman-α observations have reported an increase in geocoronal column brightness during geomagnetic storms, indicating enhanced exospheric hydrogen atom density (NH). This suggests a complex role of exospheric neutrals in determining storm-time magnetosphere dynamics and their energy release through charge-exchange processes. We developed a Model for Analyzing Terrestrial Exosphere (MATE) to investigate storm-time exospheric behaviors and their physical drivers. MATE traces test hydrogen atoms backward in time from locations in the exosphere to a nominal exobase altitude of 500 km, employing Newtonian mechanics with gravitational force. The model then calculates the phase-space densities (PSDs) of test hydrogen atoms at the exobase using the Maxwellian distribution with physics-based exobase conditions from the TIMEGCM upper atmosphere model. MATE maps PSDs at the exobase to the exosphere using Liouville’s Theorem under collisionless assumptions and derives NH by integrating the PSDs across velocity space. We conducted MATE simulation before, during, and after a minor geomagnetic storm from 12 to 18 June 2008, and compared the model results with NH estimates from the TWINS geocorona data. MATE reproduces storm-time density enhancements soon after the minimum Dst is reached, matching well with a general trend of TWINS NH estimates. The results suggest that upper atmospheric heating during a geomagnetic storm increases the number of ballistic and escaping hydrogen atoms entering the exosphere from the exobase, thereby boosting NH. However, the magnitude of modeled NH mismatches the TWINS NH estimates. The potential mechanisms of this density discrepancy include the physics excluded in the MATE model — such as neutral-neutral collisions, neutral-plasma charge exchange, solar radiation pressure, and photoionization — as well as the higher exobase hydrogen density of TIMEGCM compared to typical empirical values, which will be addressed in future.

The most abundant neutral constituent in the exospheric region (i.e., beyond ≈ 500 km altitude) is the atomic hydrogen (H); however, its density distributions predicted by physics-based models have been challenged by satellite-based observations of its far ultraviolet emissions. This discrepancy may impact magnetospheric ions’ densities and velocities since numerous chemistry and ion-neutral coupling interactions rely sensitively on the underlying neutral hydrogen population. The Polar Wind Outflow Model a first-principled model for relevant ion species in the high-latitude ionosphere, is employed to investigate the role of neutral H on the ionospheric outflow. Specifically, variability in the outflow of ionospheric H+, He+, N+, and O+ as a response to systematic enhancement and depletion of H number densities were simulated. The altitude-dependent ion density and energy partition profiles vary with neutral H density, solar activities, and ion species. These findings suggest that the exosphere plays a crucial role in controlling the production and loss of ions through ionospheric chemistry, as well as the energy contributions by altering ion-neutral-electron collisions and the ambipolar electric field to the high-latitude ionospheric outflow. As a result, the escape rates of the ionospheric outflow are directly associated with exospheric distributions. This work potentially helps understand the dominant mechanisms of atmospheric escape, particularly during a hydrogen-rich early Earth’s and exoplanet’s atmosphere, which is known to play a significant role in understanding the evolution of Earth’s atmosphere.

Upcoming heliophysics missions utilize state-of-the-art wide field-of-view (FOV) imaging technology to measure and investigate the space plasma environment on a global scale. At Earth, remote sensing of soft X-ray emissions, which are generated via the charge exchange interaction between heavy solar wind ions and exospheric neutral atoms, is a promising means to investigate the global magnetosheath structure, its response to varying solar wind conditions, and the spatiotemporal properties of the dayside magnetic reconnection. Data analysis techniques such as optical tomography can provide additional structural and time-varying information from the observed target and thus enhance the mission’s scientific return. In this work, we simulate multiple and simultaneous observations of the dayside magnetosphere using soft X-ray imagers located at long-distance vantage points to reconstruct the time-dependent, three-dimensional (3-D) structure of the magnetosheath using a dynamic tomographic approach. The OpenGCCM MHD model is used to simulate the time-varying response of the magnetosheath to solar wind conditions and, subsequently, generate synthetic soft X-ray images from multiple spacecraft vantage points separated along a common orbit. A detailed analysis is then performed to identify the nominal set of spacecraft that produces the highest fidelity tomographic reconstruction of the magnetopause. This work aims to (i) demonstrate, for the first time, the use of dynamic tomography to retrieve the time-varying magnetosheath structure and (ii) identify a nominal mission design for multi-spacecraft configurations aiming for optical tomography.

Variability in the location and shape of the dayside magnetopause is attributed to magnetic reconnection, a fundamental process that enables the transfer of mass, energy, and momentum from the solar wind into the magnetosphere. The spatial and temporal properties of the magnetopause, under varying solar and magnetospheric conditions, remain largely unknown because empirical studies using in-situ observations are challenging to interpret. Global wide field-of-view (FOV) imaging is the only means to simultaneously observe the spatial distribution of the plasma properties over the vast dayside magnetospheric region and, subsequently, quantify the energy transport from the interplanetary medium into the terrestrial magnetosphere. Two upcoming missions, ESA/CAS SMILE and NASA’s LEXI will provide wide-field imagery of the dayside magnetosheath in soft X-rays, an emission generated by charge exchange interactions between high charge-state heavy ions of solar wind origin and exospheric neutral atoms. High-cadence two-dimensional observations of the magnetosheath will allow the estimation of dynamic properties of its inner boundary, the magnetopause, and enable studies of its response to changes in the solar wind dynamic pressure and interplanetary magnetic field orientation. This work introduces a statistically-based estimation approach based on inverse theory to estimate the spatial distribution of magnetosheath soft X-ray emissivities and, with this, identify the location of the magnetopause over the Sun−Earth line. To do so, we simulate the magnetosheath structure using the MHD-based OpenGGCM model and generate synthetic soft X-ray images using LEXI’s orbit and attitude information. Our results show that 3-D estimations using the described statistically-based technique are robust against Poisson-distributed shot noise inherent to soft X-ray images. Also, our proposed methodology shows that the accuracy of both three-dimensional (3-D) estimation and the magnetopause standoff distance calculation highly depends on the observational point.

Much of what we know about the solar wind’s interaction with the Earth’s magnetosphere has been gained from isolated in-situ measurements by single or multiple spacecraft. Based on their observations, we know that reconnection, whether on the dayside magnetopause or deep within the Earth’s magnetotail, controls the bulk flow of solar wind energy into and through the global system and that nightside activity provides the energized particles that power geomagnetic storms. But by their very nature these isolated in-situ measurements cannot provide an instantaneous global view of the entire system or its cross-scale dynamics. To fully quantify the dynamics of the coupled solar wind-magnetosphere requires comprehensive end-to-end global imaging of the key plasma structures that comprise the magnetosphere which have spatial resolutions that exceeds anything possible with multi-point or constellation situ measurements. Global, end-to-end, imaging provides the pathway to understanding the system as a whole, its constituent parts, and its cross-scale processes on a continuous basis, as needed to quantify the flow of solar wind energy through the global magnetospheric system. This paper describes how a comprehensively-instrumented single spacecraft in a high-altitude, high-inclination orbit coupled with ground-based instruments provides the essential observations needed to track and quantify the flow of solar wind energy through the magnetosphere. This includes observations of the solar wind plasma and magnetic field input, the magnetopause location in soft X-rays, the auroral oval in far ultraviolet, the ring current in energetic neutrals, the plasmasphere in extreme ultraviolet, the exosphere in Lyman-α, and the microstructure of the nightside auroral oval from ground-based all sky cameras.

The exosphere is the uppermost layer of the terrestrial atmosphere, mainly composed of atomic hydrogen (H) that resonantly scatters solar far-ultraviolet (FUV) photons at 121.56 nm, also referred to as Lyman-Alpha (Ly-α) emission. Analysis of this emission has been used to determine the global, three-dimensional, and time-dependent exospheric H density structure, which is essential to assess the permanent escape of H to space as well as to determine their role in governing the transient response of terrestrial plasma environment to space weather. Thus, Ly-α emission and its by-product, the H density, are highly desirable to the magnetospheric community. On the other hand, this emission can also be regarded as a significant source of contamination during studies of FUV targets such as O/B-type stars, planetary and exoplanetary atmospheres, and the circumgalactic medium, especially when observations are acquired from Earth-orbiting instruments. In this case, accurate specification of exospheric Ly-α photon flux and its subsequent removal is required by the planetary and astrophysics community studying solar/extra-solar system objects. This work introduces EXOSpy, an open-source python-based package that provides several models of terrestrial exospheric H density and calculates exospheric Ly-α emission with a high potential to contribute to investigations in both communities. We present several examples to demonstrate how EXOSpy can be used to (i) validate current and new exospheric models based on actual Ly-α radiance data, (ii) estimate exospheric contamination for a given instrument’s line-of-sight and spatial location, and (iii) provide support for new space-based FUV instrument design.

Among end-effector robots for lower limb rehabilitation, systems based on Stewart–Gough platforms enable independent movement of each foot in six degrees of freedom. Nevertheless, control strategies described in recent literature have not been able to fully explore the potential of such a mechatronic system. In this work, we propose two novel approaches for controlling a gait simulator based on Stewart–Gough platforms. The first strategy provides the therapist direct control of each platform using movement data measured by wearable sensors. The following scheme is designed to improve the level of engagement of the patient by enabling a limited degree of control based on trunk inclination. Both strategies are designed to facilitate future studies in tele-rehabilitation settings. Experimental results have illustrated the feasibility of both control interfaces, either in terms of system performance or user subjective evaluation. Technical capacity to deploy in tele-rehabilitation was also verified in this work.

Accurate determination of plant water status is mandatory to optimize irrigation scheduling and thus maximize yield. Infrared thermography (IRT) can be used as a proxy for detecting stomatal closure as a measure of plant water stress. In this study, an open-source software (Thermal Image Processor (TIPCIP)) that includes image processing techniques such as thermal-visible image segmentation and morphological operations was developed to estimate the crop water stress index (CWSI) in potato crops. Results were compared to the CWSI derived from thermocouples where a high correlation was found ( r P e a r s o n = 0.84). To evaluate the effectiveness of the software, two experiments were implemented. TIPCIP-based canopy temperature was used to estimate CWSI throughout the growing season, in a humid environment. Two treatments with different irrigation timings were established based on CWSI thresholds: 0.4 (T2) and 0.7 (T3), and compared against a control (T1, irrigated when soil moisture achieved 70% of field capacity). As a result, T2 showed no significant reduction in fresh tuber yield (34.5 ± 3.72 and 44.3 ± 2.66 t ha - 1 ), allowing a total water saving of 341.6 ± 63.65 and 515.7 ± 37.73 m 3 ha - 1 in the first and second experiment, respectively. The findings have encouraged the initiation of experiments to automate the use of the CWSI for precision irrigation using either UAVs in large settings or by adapting TIPCIP to process data from smartphone-based IRT sensors for applications in smallholder settings.