Investigating Storm-Driven Thermospheric Density Enhancements with
Two-Line Element Sets and Orbital Propagation
Abstract
While flagship missions such as CHAMP and GOCE have shown us with
accelerometer measurements that the thermospheric density in Low Earth
Orbit (LEO) can increase by more than 200% during enhanced geomagnetic
activity, current empirical models, such as those of the MSISE and
Jacchia families, as well as the Drag Temperature Model, fail to
reproduce this behavior, limiting the ability to perform orbit
prediction and space situational awareness. Several methods have been
employed to address this dilemma. One is the High-Accuracy Satellite
Drag Model (HASDM), which uses its Dynamic Calibration Atmosphere to
employ differential correction across 75 spherical calibration
satellites to generate correction parameters to the density that are
related to 10.7 cm solar radio flux and ap (Storz et al. 2005). Doornbos
et al. 2008 has implemented a method that estimates height-dependent
scale factors to the densities from empirical models with respect to
densities directly derived from two- line element sets (TLEs). HASDM’s
reliance on Space Surveillance Network observations limit its
accessibility and detail, and Doornbos’ methods are limited by the fact
that TLEs are mean elements; densities derived from them are subject to
errors due to smoothing over an entire orbit. In addition, the method of
deriving densities from TLEs was initially done only to provide inputs
to the SGP4 orbital propagator, which was initially developed without
consideration of solar radiation pressure on the trajectory of modeled
spacecraft. We present a method to generate new model densities during
geomagnetic storms by using an in-house orbital propagator, the
Spacecraft Orbital Characterization Kit (SpOCK). This method estimates
and applies scale factors to F10.7 and a p to minimize orbit propagation
errors with TLEs. The method is tested on a variety of satellites,
including CHAMP, GOCE, and the CubeSats of the QB50 and FLOCK
constellations. This method proposes to grant insight into storm-time
thermospheric density enhancement by modeling the effects of storms on
the drag of numerous LEO spacecraft, increasing our understanding of
thermospheric dynamics and granting us improved tools for space traffic
management and thermospheric research.