Speaker
Description
The plasma environment in the inner Earth’s magnetosphere fills a vast region between Low Earth Orbit (LEO) and Geostationary Orbit (GEO) and varies significantly with solar and geomagnetic conditions on the time scales of minutes. Spacecraft surface charging is a serious concern for satellites at those orbits leading to anomalies of operations. Spacecraft charging is a function of the space environment characteristics, including sunlight/eclipse, solar activity, geomagnetic activity, electron and ion (energies <100keV) flux magnitude, and spectrum. Data may not be available at the location of the satellite to determine the cause of the anomaly.
Spacecraft design guidelines often rely on very limited data sets. Numerous observations of 1–100 keV electrons have been done at GEO. Conversely, there is a lack of statistical observations in this energy range readily available at MEO. A current need is to determine the risks that extreme events present to critical spacecrafts in GEO and MEO. An extreme event would then be outside the range of flight experience, but also beyond the engineering specifications currently in use. The way to obtain the estimates of the radiation environment at a given satellite orbit for such an event is to employ a physics-based model with close to realistic dynamics.
The Inner Magnetosphere Particle Transport and Acceleration model (IMPTAM) is a currently operating online tool (imptam.fmi.fi) driven by the real time solar wind (solar wind number density, dynamic pressure, and velocity) parameters, Interplanetary Magnetic Field (IMF), and Dst and Kp geomagnetic indices. The model provides the plasma environment (1-300 keV electron and proton differential and integral fluxes and spectra) in the near-Earth geospace covering all local times and radial distances up to 10 RE and all satellite orbits from LEO to MEO and GEO and GTO. The advantages of IMPTAM include its flexibility and module-based structure making it easy to improve the physics of particle motion in it. We present the model capabilities and results.
