Energetic electron precipitation (EEP) from the radiation belts into Earth’s atmosphere leads to several profound effects (e.g., enhancement of ionospheric conductivity, possible acceleration of ozone destruction processes). An accurate quantification of the energy input and ionization due to EEP is still lacking due to instrument limitations of low-Earth-orbit satellites capable of detecting EEP. The deployment of the ELFIN (Electron Losses and Fields InvestigatioN) CubeSats marks a new era of observations of EEP with an improved pitch-angle (0°–180°) and energy (50 keV–6 MeV) resolution. Here, we focus on the EEP recorded by ELFIN coincident with electromagnetic ion cyclotron (EMIC) waves, which play a major role in radiation belt electron losses. The EMIC-driven EEP (~200 keV – ~2 MeV) exhibits a pitch-angle distribution (PAD) that flattens with increasing energy, indicating more efficient high-energy precipitation. Leveraging the combination of unique electron measurements from ELFIN and a comprehensive ionization model known as Boulder Electron Radiation to Ionization (BERI), we quantify the energy input of EMIC-driven precipitation (on average, ~3.3x10-2 erg/cm2/s), identify its location (any longitude, 50°–70° latitude), and provide the expected range of ion-electron production rate (on average, 100–200 pairs/cm3/s), peaking in the mesosphere – a region often overlooked. Our findings are crucial for improving our understanding of the magnetosphere-ionosphere-atmosphere system as they accurately specify the contribution of EMIC-driven EEP, which serves as a crucial input to state-of-the-art atmospheric models (e.g., WACCM) to quantify the accurate impact of EMIC waves on both the atmospheric chemistry and dynamics.

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.

We present a new model designed to simulate the process of energetic particle precipitation, a vital coupling mechanism from Earth’s magnetosphere to its atmosphere. The atmospheric response, namely excess ionization in the upper and middle atmosphere, together with bremsstrahlung X-ray production, is calculated with kinetic particle simulations using the GEANT4 Monte Carlo framework. Mono-energy and mono-pitch angle electron beams are simulated and combined using a Green’s function approach to represent realistic electron spectra and pitch angle distributions. Results from this model include more accurate ionization profiles than previous analytical models, deeper photon penetration into the atmosphere than previous Monte Carlo model predictions, and predictions of backscatter fractions of loss cone electrons up to 40%. The model results are verified by comparison with previous precipitation modeling results, and validated using balloon X-ray measurements from the BARREL mission and backscattered electron energy and pitch angle measurements from the ELFIN CubeSat mission. The model results and solution techniques are developed into a Python package for public use.