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NASA NTRS2022

An ODE-Fitting Approach to Estimate Critical Aircraft Performance Parameters for Trajectory Prediction

Ground-based decision support tools (DST) in air traffic management (ATM) typically perform trajectory prediction based on aircraft performance model (APM) parameters, but some or all of these parameters might not be readily available. In particular, the three critical parameters required for trajectory prediction are the thrust setting, drag coefficients, and takeoff weight of the aircraft. Unfortunately, these parameters are coupled and appear together in physics-based kinetic models. Past approaches utilize data from a specific phase of flight (climb, level flight or descent), where one or more of the parameters are assumed to be known and estimate the remaining unknown parameters. This approach introduces bias/errors and also does not extend to scenarios where all of the above parameters are not known with sufficient accuracy. This paper is the first of its kind to propose a generalized framework for simultaneous estimation of all three critical APM parameters (thrust, drag, and mass). The proposed approach utilizes data from both the climb and descent phases and fits the ordinary differential equation for altitude in each phase using historical trajectory data available from radar tracks or ADS-B. The approach yields a set of optimized APM parameters that are best suited to fit each historical flight record. The methodology is applied on on sample flights from three different aircraft types, and the results demonstrate low fit error and consequently will yield a high level of prediction accuracy.

trajectory prediction, aircraft performance model,↗
NASA NTRS2022

Geophysical Observations Toolkit For Evaluating Coral Health (GOTECH) Fall 2021 Final Report

The NASA Langley Research Center (LaRC) Data Science Team (DST), under the Office of the Chief Information Officer (OCIO), is investigating the capacity of the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite to infer the vitality of coral reefs. This report describes the Fall 2021 period of performance for the Geophysical Observations Toolkit for Evaluating Coral Health (GOTECH) project. During this effort, two student teams at Georgia Tech developed machine-learning models to predict the vitality of coral reefs in targeted geographic regions based on backscatter data from the CALIPSO satellite. To train these models, students fused data to form a common operating picture of how coral reefs have grown and decayed worldwide. This report describes the student assignment, background, and results of the semester's research.

Machine Learning↗
NASA NTRSDate not supplied

An ODE-Fitting Approach to Estimate Critical Aircraft Performance Parameters for Trajectory Prediction

Ground-based decision support tools (DST) in air traffic management (ATM) typically perform trajectory prediction based on aircraft performance model (APM) parameters, but some or all of these parameters might not be readily available. In particular, the three critical parameters required for trajectory prediction are the thrust setting, drag coefficients, and takeoff weight of the aircraft. Unfortunately, these parameters are coupled and appear together in physics-based kinetic models. Past approaches utilize data from a specific phase of flight (climb, level flight or descent), where one or more of the parameters are assumed to be known and estimate the remaining unknown parameters. This approach introduces bias/errors and also does not extend to scenarios where all of the above parameters are not known with sufficient accuracy. This paper is the first of its kind to propose a generalized framework for simultaneous estimation of all three critical APM parameters (thrust, drag, and mass). The proposed approach utilizes data from both the climb and descent phases and fits the ordinary differential equation for altitude in each phase using historical trajectory data available from radar tracks or ADS-B. The approach yields a set of optimized APM parameters that are best suited to fit each historical flight record. The methodology is applied on on sample flights from three different aircraft types, and the results demonstrate low fit error and consequently will yield a high level of prediction accuracy.

trajectory prediction↗
NASA NTRS2022

Explicit IMF By-Dependence of Energetic Protons and the Ring Current

The most important parameter driving the solar wind-magnetosphere interaction is the southward (Bz) component of the interplanetary magnetic field (IMF). While the dawn-dusk (By) component of the IMF is also known to play an important role, its effects are usually assumed to be independent of its sign. Here we demonstrate for the first time a seasonally varying, explicit IMF By-dependence of the ring current and Dst index. Using satellite observations and a global magnetohydrodynamic model coupled with a ring current model, we show that for a fixed level of solar wind driving the flux of energetic magnetospheric protons and the growth-rate of the ring current are greater for By < 0 (By > 0) than for By > 0 (By < 0) in Northern Hemisphere summer (winter). While the physical mechanism of this explicit By-effect is not yet fully understood, our results suggest that IMF By modulates magnetospheric convection and plasma transport in the inner magnetosphere.

L Holappa↗
NASA NTRSDate not supplied

Multi-Star Wavefront Control: Update on Technology Development for Roman Space Telescope and Habitable Worlds Observatory

A majority of Sun-like stars have at least one stellar companion that can introduce additional noise into the field of view of any high-contrast imaging instrument, limiting the achievable contrast. These include high-quality target stars such as the A and B components of Alpha Centauri, our nearest stellar neighbor. Enabling direct imaging of binary stars has the potential to increase the scientific yield for coronagraphic instruments planned on NASA's future space missions and concepts, including the Roman Space Telescope and the Astro2020 IR/O/UV flagship. Multi-Star Wavefront Control (MSWC) is a wavefront-control technique that simultaneously removes the (mutually incoherent) stellar leakage from both stellar components, enabling direct imaging of planets in many binary star systems. MSWC is an algorithmic technique and can be used with existing wavefront control systems on coronagraphic instruments (as well as starshades if a deformable mirror is available in the optical path) including planned observations on the upcoming PICTURE-D balloon flight. We report on the latest experimental and numerical results obtained with MSWC as part of the technology development effort to demonstrate compatibility with existing high-contrast imaging platforms for this technique. We first report on functional tests carried out at Subaru's SCExAO instrument operating in-air and showing the sub-Nyquist mode at 4.1e-6 contrast in monochromatic light. The Super-Nyquist regime of MSWC was recently tested in vacuum at JPL's High Contrast Imaging Testbed (HCIT) on the Decadal Survey Testbed (DST) reaching 8.6e-9 contrast in a 10% band. We also report on results for the current stage of vacuum testing at HCIT's Occulting Mask Coronagraph (OMC) testbed using a mask similar to the contributed MSWC mask on the Roman Space Telescope's coronagraph instrument which has demonstrated suppression at the 9.8e-9 contrast at Super-Nyquist separations around the 3rd diffraction order and is planned to use a novel binary source simulator.

high-contrast imaging↗
NASA NTRS2022

Determining Latitudinal Extent of Energetic Electron Precipitation Using MEPED On-Board NOAA/POES

Energetic Electron Precipitation (EEP) from the plasma sheet and the radiation belts ionizes the polar lower thermosphere and mesosphere. EEP increases the production of NO x and HO x , which will catalytically destroy ozone, an important element of atmospheric dynamics. Therefore, measurement of the latitudinal extent of the precipitation boundaries is important in quantifying the atmospheric effects of the Sun-Earth interaction. This study uses measurements by the Medium Energy Proton Electron Detector (MEPED) of six NOAA/POES and EUMETSAT/METOP satellites from 2004 to 2014 to determine the latitudinal boundaries of EEP and their variability with geomagnetic activity and solar wind drivers. Variation of the boundaries for different electron energies and Magnetic Local Time (MLT) is studied. Regression analyses are applied to determine the best predictor variable based on solar wind parameters and geomagnetic indices. The highest correlation was found for the pressure-corrected Dst index when applying a linear regression model. A model of the equatorward EEP boundary is developed separately for three different energy channels, >43, >114, and >292 keV, and for 3 hour MLT sectors. For >43 keV EEP, 80% of the equatorward boundaries predicted by the model are within ±2.2° cgmlat. The model exhibits a solar cycle bias where it systematically exaggerates the equatorward movement of the EEP region during solar minimum. The highest accuracy of the model is found in periods dominated by corotating interaction regions/high speed solar wind streams. The result will be a key element for constructing a model of EEP variability to be applied in atmosphere climate models.

E. M. Babu↗
NASA NTRS2021

ExEP: Initial super-Nyquist wavefront control experiments in the Decadal Survey Testbed

In order to characterize exoplanets around nearby stars, upcoming and proposed space telescopes are being designed with high contrast coronagraph instruments. Coronagraphs are generally designed to suppress only a single, on-axis star, but there are numerous binary star systems within our observational range. Multi-star wavefront correction (MSWC) is a technique that uses deformable mirror(s) to simultaneously suppress light from more than one star to create a high contrast dark zone in the image. MSWC has already been well demonstrated in simulation and in air-based testbeds. In this paper, we describe our prepatory vacuum experiments in the Decadal Survey Testbed (DST) at the Jet Propulsion Laboratory. First we implemented super-Nyquist wavefront control (SNWC, a critical component of MSWC), and then we proceeded to simultaneous sub- and super-Nyquist control. With our existing calibration methods, SNWC reached a contrast of $8.6{\times}10^{-9}$ in a 10\% bandpass around a first-order diffraction spot; calibration improvements are needed to improve model agreement for higher-order spots. We have also implemented changes to our software (the open-source package FALCO) required for MSWC, and identified the necessary changes in hardware. Here we report our best SNWC lab results and our plans for implementing MSWC during a future set of experiments.

Bendek, Eduardo↗
NASA NTRSDate not supplied

The Circulation of the Plasmasphere Fluid during the Erosion Event on September 8, 2017

A strong solar wind pressure pulse triggered the magnetic storm on September 7, 2017. Near the end of September 7, the z-component of the interplanetary magnetic field (IMF Bz) dropped from 9 to -10 nT in 30 min. The IMF Bz remained at the level of -10 nT for 2 hours and then had another rapid drop to -31 nT in 30 min. The sudden plunge of IMF Bz and the associated strong convection electric field stirred up the storm main phase with Dst falling from 0 to -122 nT from 2200 UT on September 7 to 0200 UT on the 8th. Severe plasmasphere erosion was observed on September 8 by multiple spacecraft, such as the Van Allen Probes and the Arase satellite. In this study, we examine the fate of the eroded plasmasphere particles during this event by model simulation as well as satellite data analysis. The simulation tool we use is the Space Weather Modeling Framework (SWMF)/Block-Adaptive Tree Solarwind Roe-type Upwind Scheme (BATS-R-US) model coupled with the Comprehensive Inner Magnetosphere-Ionosphere (CIMI) model. One of the distinctive capabilities of the SWMF/BATSRUS-CIMI model is that it treats the cold plasmas in the plasmasphere as a separate fluid in the MHD equations. As a result, the transport and circulation of the plasmasphere fluid in the global magnetosphere can be traced and the impacts of this cold fluid on the global magnetosphere can be evaluated. In this paper, we will show how the drainage plume is formed during the storm and how the plasmasphere fluid is transported to the flank and lobe regions and eventually to the plasma sheet and reenters into the plasmasphere. We will validate our simulation by plasmasphere signatures observed in both the inner and outer magnetosphere.

Mei-Ching Fok↗
NASA NTRSDate not supplied

Small Events Involve the Entire Solar Atmosphere

Here we discuss and analyze observations centered on a bipolar region of enhanced-network magnetic flux near disk center on SOL2017-03-17T14:00-17:00. The comprehensive data set comprises observations from SDO:HMI,AIA; Hinode:SOT, XRT; DST:IBIS, FIRS; ALMA; and IRIS, thus providing a variety of plasma diagnostics spanning the photosphere to the corona. We confirm the correspondence between the broadest width of the hydrogen-α spectral line and the hottest temperatures observed in millimeter wavelengths, which persist for the duration of cotemporal observations. We use these data to study the existence and persistence of oscillatory power with periods in the 3 to 5 minute range. Previous studies have found conflicting results on the existence of these modes in the ALMA data, which we suggest is linked to the spectral windowing due to requisite calibration observations. We also find that spatial maps of oscillatory power at 3mm display the pattern of magnetic shadows and halos typically displayed by other chromospheric diagnostics. Finally, numerous transient brightenings were observed across the data set, and here we highlight transient brightenings within a set of thin filamentary features. One interesting event shows initial heating in the cooler (ALMA, 7000 K) before showing in the hotter (XRT, 3 MK) data series.

Adam Kobelski↗
NASA NTRS2022

Stormtime Ring Current Heating of the Ionosphere and Plasmasphere

The energy deposition from ring current ions into the high density “cold” plasma of the ionosphere and plasmasphere is analyzed, based on a Comprehensive Inner Magnetosphere-Ionosphere simulation of the 2015 October 7 storm. In addition, the Naval Research Laboratory Sami3 is Also a Model of the Ionosphere ionosphere/plasmasphere code is used to simulate the effect of Coulomb-collision heating of plasmasphere and ionosphere electrons by ring current ions. We find that, during stormtime peaks in the Dst index, energy is deposited at altitudes as low as 100 km. Heating along the entirety of any given field line, both in the ionosphere and plasmasphere, contributes to increased temperatures in the ionosphere F layer and inner magnetosphere and to subsequent cold O + outflows. However, relative to the heating of the plasmasphere, the direct heating of the ionosphere by ring current ions produces only small effects. Qualitative model-data agreement on the N + /O + density ratio is consistent with the hypothesis that these outflows are driven by thermal forcing.

J. Krall↗
NASA NTRSDate not supplied

Even Small Events Involve the Entire Solar Atmosphere

The connection between the photosphere, chromosphere, and corona is essential for understanding the energy flows throughout the solar atmosphere. Here we discuss and analyze observations centered on a bipolar region of enhanced-network magnetic flux near disk center on SOL2017-03-17T14:00-17:00. The comprehensive data set comprises observations from SDO: HMI, AIA; Hinode: SOT, XRT; DST: IBIS, FIRS; ALMA; and IRIS; thus providing a variety of plasma diagnostics spanning the photosphere to the corona. Numerous transient brightenings were observed across the data set, and here we highlight transient brightenings within a set of thin filamentary features. One interesting event shows initial heating in the cooler (ALMA, 7000 K) before showing in the hotter (XRT, 3 MK) data series. These brightenings showcase how even small events involve large ranges of the solar atmosphere.

chromosphere↗
NASA NTRSDate not supplied

Machine Learning Approach for Aircraft Performance Model Parameter Estimation for Trajectory Prediction Applications

Inaccurate prediction of aircraft trajectory by ground-based decision support tools (DST) is a major concern in air traffic management (ATM). Aircraft trajectory prediction tools rely on a simplified point-mass aircraft performance model (APM) to make their predictions. Even though the performance coefficients and weight of an aircraft are a vital part of the APM’s predictions and accuracy, these coefficients are proprietary in nature and therefore, unavailable to DSTs. Current ATM research focuses on improving the estimate of some APM parameters by freezing all other coefficients. This simplified approach introduces unwanted sources of bias and negatively impacts the accuracy of the performance model. In this paper, we apply machine learning (ML) techniques for the simultaneous prediction of three key APM parameters (two drag coefficients and the initial aircraft weight). To accomplish this, we employ an ordinary differential equation (ODE) fitting approach to generate optimized APM parameter labels customized to each individual flight record. Subsequently, we train ML models to capture the relationship between the historical data and the optimized APM parameters. Two different ML model solutions are applied and APM coefficients are predicted for unseen flights. The results indicate that the ML models are able to capture the relationship between APM parameters and flight-related features with good accuracy.

trajectory prediction, machine learning, aircraft ↗
NASA NTRSDate not supplied

Manual Crew Override of Vehicle Landings Following G-Transitions

BACKGROUND Manual control during exploration spaceflight consists of both planned automated supervisory control and unplanned crew override. This crew override capability is critical to enable overall mission success during landing contingencies. However, the introduction of manual override capabilities must be implemented to enable crews to mitigate risks introduced by human error. Adaptive changes in the sensorimotor system can manifest during g-transitions as spatial disorientation. While training and landing aids enable successful landing through disorientation, these adaptive changes may increase cognitive demand that needs to be accounted for in the manual control strategy. It is important to characterize these effects as soon as possible following the G-transition to develop appropriate countermeasures. METHODS In this study, we will examine operational piloting tasks following International Space Station (ISS) missions in a simulated lunar landing using a six-degree-of-freedom (6DOF) motion base. The motion-based simulation will be implemented in our laboratory at the Johnson Space Center (JSC) and will be available within hours following the return from commercial crew landings. The primary goals of this study are (1) to understand the impact of spaceflight on crew ability to perform manual crew override tasks, (2) to examine how adaptive changes in vestibular and cognitive function relate to changes in manual crew override proficiency, and (3) compare performance during late “just-in-time” on-board training with early post-flight crew performance. The impact of spaceflight on piloting capability will be assessed from pre- versus post-flight changes in crewmembers assigned to either short duration (< 30 day) or long duration (~6- month) missions to the International Space Station (ISS). Individual differences in post-flight vestibular and cognitive changes include motion sickness reports, measures of tilt motion perception accuracy and precision, and dual-task tracking. During the 6DOF lunar simulation, the crew will manually takeover attitude and rate-of-descent to the nominal or re-designated landing aim point during the approach phase. The outcome measures for the lunar crew override tasks will be the percent time maintaining actual vehicle states, e.g., attitude and rate-of-descent, within recommended guidance during the landing approach, number and maximum deviation outside limits, and root mean square error (RMSE). Given that “just-in-time” (JIT) training is an operational expectation for the Human Landing System (HLS) program, all participants will perform late inflight JIT training for each manual crew override task in which they will participate. Crew proficiency will be captured inflight during JIT training that will be implemented on a laptop with hand controllers to allow the crewmember to practice the landing task procedures like the approach implemented for JIT training with Shuttle landing and ISS telerobotic tasks. COUNTERMEASURE UPDATES The lunar lander simulation has been implemented onto a two-laptop display system where subjects select from alternative landing points, based upon avoiding hazards that the on-board system identifies during the landing. The subject makes inputs using a rotational hand controller (i.e., joystick) and a translational hand controller, which are processed by simulated vehicle dynamics to update the vehicle attitude and rate of descent. Subjects will utilize a combination of flight, situation, and status displays to monitor the state of the simulated vehicle. The simulation exports tilt and translation movements to a 6DOF motion base synced to visual movements and provides representative vestibular cues to the subject while performing the task inside an enclosed cabin featuring a simulated lunar out-the-window view and a heads-down lander cockpit view. RELEVANCE This project will deliver an operational demonstration of crew override capability following spaceflight and identify potential deficits that may require remediation. Comparison of individual vestibular and cognitive changes with crew override performance will help better characterize the manual control risks associated with sensorimotor alterations. The inclusion of “just-in-time” on-board training will ensure we are characterizing changes in override proficiency with this expected countermeasure in place. ACKNOWLEDGEMENTS: The authors acknowledge contributions from Draper, HLS Joint Test Panel, Crew HLS Interfaces for Piloting Working Group, and Dynamic Skills Trainer (DST) Lab toward the development of the lunar landing simulation. This project is funded by the Human Health Countermeasures Element.

Austin M Bollinger↗
NASA NTRSDate not supplied

A New Integral Field Spectrograph for Broadband Coronagraph Demonstrations at the High Contrast Imaging Testbed Facility

An integral field spectrograph (IFS) camera may help fulfill the exoplanet characterization goals of a future Habitable Worlds Observatory. During the Nancy Grace Roman Space Telescope mission formulation phase, the Coronagraph Instrument Project established the laboratory performance baseline of a combined coronagraph and IFS system with the Prototype Imaging Spectrograph for Coronagraphic Exoplanet Studies (PISCES; 1E-8 contrast over an 18% bandpass; 3--9 lambda/D bowtie-shaped control region). New laboratory demonstrations are needed to expand on this milestone in terms of contrast, bandpass, and field of view towards the requirements of a future mission capable of characterizing the atmospheres of Earth-like exoplanets. Here we present the design of a successor to PISCES that can observe a 20 lambda/D-diameter field of view with an instantaneous bandpass up to 30%, at a resolving power R > 70 at visible wavelengths. This instrument will interface with the existing coronagraph layout in the High Contrast Imaging Facility DST-2 vacuum chamber. The addition of a spectroscopic imaging camera at HCIT will benefit the wider coronagraph technology community by enabling other NASA-supported investigators to automatically obtain multi-wavelength measurements of speckles both inside and outside of their control region, and the instrument will support community-led demonstrations of high-order wavefront sensing and control techniques such as dark hole maintenance and linear dark field control.

coronagraph↗
NASA NTRSDate not supplied

The Circulation of the Plasmasphere Fluid during the Erosion Event on September 8, 2017

A strong solar wind pressure pulse triggered the magnetic storm on September 7-8, 2017. Near the end of September 7, the z-component of the IMF Bz dropped from 9 to -10 nT in 30 min and then had another rapid drop to -31 nT in 30 min. The sudden plunge of IMF Bz and the associated strong convection electric field stirred up the storm main phase with Dst falling from 0 to -122 nT from 2200 UT on September 7 to 0200 UT on the 8th. Severe plasmasphere erosion was observed on September 8 by multiple spacecraft, such as the Van Allen Probes and the Arase satellite. In this study, we examine the fate of the eroded plasmasphere particles during this event by model simulation as well as satellite data analysis. The simulation tool we use is the SWMF/BATS-R-US model coupled with the CIMI model. The cold plasmas in the plasmasphere is treated as a separate fluid in the MHD equations. As a result, the transport and circulation of the plasmasphere fluid in the global magnetosphere can be traced and the impacts of this cold fluid on the global magnetosphere can be evaluated. In this paper, we will show how the drainage plume is formed during the storm and how the plasmasphere fluid is transported to the flank and lobe regions and eventually to the plasma sheet and reenters into the inner magnetosphere. We will validate our simulation by plasmasphere signatures observed in both the inner and outer magnetosphere.

Mei-Ching Fok↗
NASA NTRSDate not supplied

Manual Crew Override of Vehicle Landings Following G-Transitions

BACKGROUND Manual control during exploration spaceflight consists of both planned automated supervisory control and unplanned crew override. This crew override capability is critical to enable overall mission success during landing contingencies. However, the introduction of manual override capabilities must be implemented to enable crews to mitigate risks introduced by human error. Adaptive changes in the sensorimotor system can manifest during g-transitions as spatial disorientation. While training and landing aids enable successful landing through disorientation, these adaptive changes may increase cognitive demand that needs to be accounted for in the manual control strategy. It is important to characterize these effects as soon as possible following the G-transition to develop appropriate countermeasures. METHODS The following study seeks to inform the risk associated with altered sensorimotor and vestibular function impacting critical mission tasks. We aim to characterize the effects of short and long-duration weightlessness on manual control following G-transitions using simulated lunar landing on a six-degree-of-freedom (6DOF) motion base, a fixed base simulation, and a supervisory control tablet task. The primary goal is to understand the impact of spaceflight on crew ability to perform manual crew override and supervisory control. This aim will be assessed by comparing pre- versus postflight simulation performance in crewmembers assigned to either short duration (< 30 day) or long duration (~6- month) missions to the International Space Station (ISS). We hypothesize there will be postflight increases in the percent time that pilots are outside of the acceptable range for recommended vehicle state parameters and the reaction time for secondary cognitive tasks. Ground-based control subjects, who are demographically matched to the crew considering age (± 5 years) and gender, will undergo the same testing schedule as the crew to examine the effects of flight phase independent of microgravity exposure. The second aim is to examine how adaptive changes in vestibular and cognitive function relate to changes in manual crew override proficiency. Crew performance for a sensorimotor perceptual test battery will evaluate motion perception tracking, roll nulling, and/or vection sensitivity using the 6DOF motion base. We hypothesize that a higher severity of vestibular alterations will be associated with increased percent time outside of guidance limits. Motion sickness severity and sleepiness will also be evaluated. To determine the impact of “just-in-time” training, the third aim seeks to compare performance during on-board lunar landing tasks conducted late in-flight to early postflight. We hypothesize that proficiency on the “just-in-time” laptop trainer late in mission will be positively correlated with early postflight proficiency on the same task. The final aim will establish assessments of performance, training protocols, and the learning progression in a ground-control cohort of first-time users. RESULTS The assessment of the learning progression associated with the piloting task on the motion base system with thirty ground subjects will be reported. Learning curves will be established across four distinct sessions and within session considering trial difficulty. The difficulty of the landing task can be modulated with the landing divert distance and cross or downrange difficulty. Results may include changes in performance across multiple trials of a multi-attribute lunar tablet supervisory control task. Preliminary investigations of eighteen subjects who completed vestibular threshold and motion perception tasks offer expected performance ranges for upcoming preflight crew evaluations. The results yielded an average roll threshold of 0.46 ± 0.30 deg/s and an average roll nulling root mean square error performance of 2.52 ± 0.52 deg/s. RELEVANCE This project will deliver an operational demonstration of crew monitoring capability following spaceflight and identify potential deficits that may require remediation. Comparison of individual vestibular and cognitive changes with crew performance will help better characterize the manual control risks associated with sensorimotor alterations. Ground testing will evaluate learning progression, refine training protocols, and serve as a control cohort for comparisons to crew performance. ACKNOWLEDGEMENTS: The authors acknowledge contributions from Draper, the Dynamic Skills Trainer (DST) Lab, and the Software, Robotics, and Simulation Division toward the development of the lunar landing simulation platforms. This project is funded by the Human Health Countermeasures Element.

Hannah M. Weiss↗
NASA NTRS2024

Storm-Time Variability of Terrestrial Hydrogen Exosphere: Kinetic Simulation Results

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 neutralneutral 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.

Hyunju K Connor↗