Atmospheric neutral density is a crucial component to accurately predicting and tracking 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 (1) slow solar indices, (2) high cadence solar irradiance, and (3) combined high-cadence solar irradiance and geomagnetic indices. 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. 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.

This study focuses on utilizing the increasing availability of satellite trajectory data from global navigation satellite system-enabled low-Earth orbiting satellites and their precision orbit determination (POD) solutions to expand and refine thermospheric model validation capabilities. The research introduces an updated interface for the GEODYN-II POD software, leveraging high-precision space geodetic POD to investigate satellite drag and assess density models. This work presents a case study to examine five models (NRLMSIS2.0, DTM2020, JB2008, TIEGCM, and CTIPe) using precise science orbit (PSO) solutions of the Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2). The PSO is used as tracking measurements to construct orbit fits, enabling an evaluation according to each model’s ability to redetermine the orbit. Relative in-track deviations, quantified by in-track residuals and root-mean-square errors (RMSe), are treated as proxies for model densities that differ from an unknown true density. The study investigates assumptions related to the treatment of the drag coefficient and leverages them to eliminate bias and effectively scale model density. Assessment results and interpretations are dictated by the timescale at which the scaling occurs. JB2008 requires the least scaling (~-23%) to achieve orbit fits closely matching the PSO within an in-track RMSe of 9 m when scaled over two weeks and 4 m when scaled daily. The remaining models require substantial scaling of the mean density offset (~30-75%) to construct orbit fits that meet the aforementioned RMSe criteria. All models exhibit slight over or under sensitivity to geomagnetic activity according to trends in their 24-hour scaling factors.

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The habitability of the surface of any planet is determined by a complex evolution of its interior, surface, and atmosphere. The electromagnetic and particle radiation of stars drive thermal, chemical and physical alteration of planetary atmospheres, including escape. Many known extrasolar planets experience vastly different stellar environments than those in our Solar system: it is crucial to understand the broad range of processes that lead to atmospheric escape and evolution under a wide range of conditions if we are to assess the habitability of worlds around other stars. One problem encountered between the planetary and the astrophysics communities is a lack of common language for describing escape processes. Each community has customary approximations that may be questioned by the other, such as the hypothesis of H-dominated thermosphere for astrophysicists, or the Sun-like nature of the stars for planetary scientists. Since exoplanets are becoming one of the main targets for the detection of life, a common set of definitions and hypotheses are required. We review the different escape mechanisms proposed for the evolution of planetary and exoplanetary atmospheres. We propose a common definition for the different escape mechanisms, and we show the important parameters to take into account when evaluating the escape at a planet in time. We show that the paradigm of the magnetic field as an atmospheric shield should be changed and that recent work on the history of Xenon in Earth’s atmosphere gives an elegant explanation to its enrichment in heavier isotopes: the so-called Xenon paradox.

On 7 January 2014, a solar storm erupted, which eventually compressed the Earth’s magnetosphere leading to the generation of chorus waves. These waves enhanced local wave-particle interactions and led to the precipitation of electrons from 10s eV to 100s keV. This paper shows observations of a low energy cutoff in the precipitation spectrum from Van Allen Probe B Helium Oxygen Proton Electron (HOPE) measurements. This low energy cutoff is well replicated by the predicted loss calculated from pitch angle diffusion coefficients from wave and plasma observations on Probe B. To our knowledge, this is the first time a single spacecraft has been used to demonstrate an accurate theoretical prediction for chorus wave-induced precipitation and its low energy cutoff. The specific properties of the precipitating soft electron spectrum have implications for ionospheric activity, with the lowest energies mainly contributing to thermospheric and ionospheric upwelling, which influences satellite drag and ionospheric outflow.

Observations of energetic charged particles associated with Io’s footprint (IFP) tail, and likely within or very near the Main Alfvén Wing, during Juno’s 12th perijove (PJ) crossing show evidence of intense proton acceleration by wave-particle heating. Measurements made by Juno/JEDI reveal proton characteristics that include pitch angle distributions concentrated along the upward loss cone, broad energy distributions that span ~50 keV to 1 MeV, highly structured temporal/spatial variations in the particle intensities, and energy fluxes as high as ~100 mW/m2. Simultaneous measurements of the plasma waves and magnetic field suggest the presence of ion cyclotron waves and transverse Alfvénic fluctuations. We interpret the proton observations as upgoing conics likely accelerated via resonant interactions with ion cyclotron waves. These observations represent the first measurements of ion conics associated with moon-magnetosphere interactions, suggesting energetic ion acceleration plays a more important role in the IFP tail region than previously considered.

While Jupiter’s gravity strongly binds the neutral atmosphere to the planet, energization in the auroral region can lead to field-aligned upward transport and escape of electrons and ions. This field-aligned transport mechanism provides a way for heavier ions like H2+ and H3+ to enter Jupiter’s magnetosphere. Formation of H3+ from H2+ occurs quickly in the collisional ionosphere, so rapid field-aligned transport of H2+ is the most likely mechanism for H2+ ions present in Jupiter’s high-latitude ionosphere and magnetosphere. We model these processes using the PWOM model for ionospheric field-aligned transport and J-GITM providing the neutral atmosphere and lower ionospheric boundary. The ionosphere is formed and heated by a combination of solar EUV flux and electorn precipitaiton. The effects of energization from electron precipitation and resonant wave heating are also accounted for. We show the energy input that is needed to produce ion escape in both the fluid and kinetic regimes, and we show the formation of ion conics in the kinetic PWOM model. We discuss what observations from JUNO are needed to allow us to constrain and test our model results.