Sean Elvidge, University of Birmingham; Matthew Brown, University of Birmingham
Keywords: space weather, thermosphere, modeling, upper atmosphere, operations
Abstract:
The proliferation of satellite technologies and their critical role in modern communications, navigation, and Earth observation underscores the importance of safeguarding space assets, particularly in the congested orbits of Low Earth Orbit (LEO). The increasing congestion in LEO heightens the risk of satellite collisions, posing a significant threat to the operational safety and longevity of space-based assets. In this context, the development and deployment of advanced atmospheric models are paramount for accurate orbit prediction and collision risk mitigation. For operational use in the UK the Advanced Ensemble electron density Assimilation System (AENeAS; Elvidge & Angling, 2019) is being deployed to support effort in this direction, developed to enhance Space Situational Awareness (SSA) and Space Domain Awareness (SDA) through improved orbit determination and conjunction analysis.
AENeAS is a physics-based data assimilation model that focuses on the coupled ionosphere-thermosphere system, employing the local ensemble transform Kalman filter (LETKF) for its data assimilation processes. The model’s strength lies in its comprehensive assimilation of various data sources, including electron density true height profiles from ionosondes, total electron content (TEC) measurements from global navigation satellite system (GNSS) receivers, radio occultation observations, and derived neutral densities from satellite accelerometers. Furthermore, AENeAS’s capability to integrate additional thermospheric observations, such as two-line element (TLE) data and orbital radar information, significantly enhances its ability to accurately specify the thermosphere’s effects on satellite trajectories. This comprehensive approach to data assimilation ensures that AENeAS can provide highly accurate and reliable forecasts, critical for the safe operation of satellites in LEO.
Operational deployment of AENeAS at the UK Met Office will provide satellite operators with real-time assessments (nowcasts) of the thermosphere, along with actionable forecasts. These forecasts are invaluable for the decision-making processes related to collision avoidance, thereby enhancing the safety and operational longevity of satellites. The improved specification of the thermosphere through the AENeAS model significantly reduces uncertainties in orbit determination. By offering more precise density estimates, satellite operators can predict satellite positions and velocities with greater confidence, leading to a reduction in false collision alarms. This increased accuracy in orbit prediction also facilitates the minimization of unnecessary orbit manoeuvres, thereby conserving fuel and extending the satellites’ operational lifetime.
The paper details the innovative assimilation of novel thermospheric observations in the AENeAS model, highlighting the incorporation of TLE data and orbital radar information alongside the extensive ionospheric observations typically assimilated. The integration of such diverse observations into the AENeAS model underscores its uniqueness and utility in addressing the challenges of SSA/SDA. Moreover, the paper outlines the suite of products, tools, and services that the AENeAS model facilitates. These include real-time nowcasts and forecasts of the thermosphere and ionosphere, providing critical information on neutral densities, electron densities, and ion-neutral winds and temperatures. In addition, the model provide realistic uncertainty estimates of its parameters (not necessarily Gaussian), satellite operators can leverage these predictions to refine collision avoidance strategies. The availability of these resources through the AENeAS model significantly contributes to creating a safer and more sustainable operational environment for satellite-based technologies.
Finally, validation of the AENeAS model is presented, demonstrating its performance in comparison to empirical models like NRLMSIS 2.0, DTM-2020, other first-principles models and the empirical-based data assimilation model HASDM. Validation efforts utilize independent data sources, such as the Swarm and CHAMP satellites, to assess the accuracy of the model’s predictions. These results reveal that AENeAS, bolstered by the novel thermospheric observations it assimilates, can offer more accurate estimates of the neutral density state than competing models. This validation underscores the significant value of the AENeAS model in supporting satellite operations within the domain of SSA/SDA, illustrating its critical role in enhancing the safety, reliability, and sustainability of space operations amidst the growing challenges of space congestion.
Date of Conference: September 17-20, 2024
Track: Atmospherics/Space Weather