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arXiv · 2209.05597

Understanding variability in HASDM to support space traffic management

Abstract

With more commercial constellations planned, the number of Low Earth Orbit (LEO) objects is set to TRIPLE in two years. The growth in LEO objects directly increases the probability of unintentional collisions between objects due to accumulating space debris. Effective space traffic management needs accurate knowledge of the variability in upper atmosphere densities. Data assimilative modeling, where physics-based models are informed by measurements, supplies the best capability today for specifying and predicting space weather. The foundation for this modeling comes from the SET High Accuracy Satellite Drag Model (HASDM) density database. We report on studies to understand the variabilities in HASDM. We identify two thermospheric features from the SET HASDM density database. First, we have confirmed that the time scale is very rapid (1-hour) for molecular conduction above 200 km to transfer energy vertically in the thermosphere. This results couples with a longer timescale for conduction in the 100-200 km region where it takes up to 2 days for energy to transition across that region via molecular conduction. We now have an excellent picture of the timescales of energy change throughout the thermosphere. Second, the SET HASDM density data display a common range of variability despite the level of daily averaged geomagnetic activity as represented by Ap. During higher levels of daily averaged geomagnetic activity, the density mean and median values increase at all altitude levels. However, the relative range of variability is consistent from one daily average of Ap to the next. The reason is likely to be that the underlying pre-storm density of the thermosphere is determined by the solar EUV and FUV irradiances that create a thermal foundation of the upper atmosphere. The daily averaged geomagnetic activity is a perturbation upon that foundation.

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W. Kent Tobiska, Marcin D. Pilinski, Shaylah Mutschler, Kaiya Wahl, Jean Yoshii, Dave Bouwer, Piyush Mehta, Richard Licata. 2022-09-12. Understanding variability in HASDM to support space traffic management. https://arxiv.org/abs/2209.05597

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