Thesis
Physical Understanding and Forecasting of the Thermospheric Structure and Dynamics
Timothy Kodikara (2019). Doctoral dissertation. RMIT University, Melbourne, Australia
What is it about?
Radiation from the Sun drives, for the most part, the variations in temperature and energy in the thermosphere, which is the region of space approximately between 80 and 700 km altitudes. Despite decades of progress in upper atmospheric research, developing a precise model of the thermosphere remains a significant challenge. One motivation to better understand the thermosphere is the growing number of satellites in the region. A prime requirement for the management of satellites (and therefore, space-based services and technologies) is to avoid satellite collisions, which requires the capability to precisely track and predict their orbits. The unpredictability attached to the safety of operational satellites and human space operations in the near-Earth orbit is higher than ever due to the increasing anthropogenic space debris that orbits alongside. In this enterprise of orbit tracking and prediction, the most significant uncertainty in the low Earth orbit region (160-2,000 km altitudes) originates from the poor estimation of atmospheric mass density vis-á-vis atmospheric drag.
Why is it important?
Severe space weather events not only have the potential to damage satellites, disrupt navigation and communication systems, and cause power grid outages but also pose a radiation hazard to human space operations. Almost every aspect of our economy—navigation, agriculture, security, banking, and healthcare, is linked, driven, and sustained by space-based technologies. Recovery from socioeconomic disruptions to such services (and collateral effects) can take anywhere from days, months to years. Understanding and prediction of these events require the knowledge of the multi-scale and multi-physics Sun-Earth system.
Perspectives
We have made a substantial and remarkable progress in modelling the Earth's upper atmosphere. The progress is substantial because today we can combine many models to simulate the geospace environment from the Sun’s core to Earth and get a reasonably good picture of the reality. Remarkable is the accuracy, resolution, and predictive capabilities of the models that have improved over the years. There is still a need for better and accurate predictive models mainly due to the nature of the applications—the rise in applications with the requirements of high accuracy, and the lack of a complete picture of the physical system. The more we understand about the upper atmosphere, the better our predictions of its state will be.
