Global-scale observations allow us unparalleled instantaneous views of the solar-terrestrial system. Instruments that provide global views are not new, with spacecraft such as IMAGE and Polar providing hemisphere-wide auroral images, and SuperDARN providing maps of ionospheric convection. However, in the last decade the availability of this data has improved, with SuperDARN expanding to ever-lower latitudes and datasets such as AMPERE and SuperMAG providing views of Earth’s ionospheric electrodynamics which were previously unattainable. In turn, our modeling capability has improved with the ability to compare model outputs to these observations. Machine learning can lever these global-scale observations, and forthcoming missions such as ESA’s SMILE will increase the data we have at these scales.
This session brings together work which examines the coupled ionosphere-thermosphere system on a global scale. This includes abstracts focusing on global-scale spacecraft missions, from currently operational data to those in the early phases. Anyone working below the magnetosphere is very welcome to submit. We invite observers using space-based observations or ground-based instrumentation (such as magnetometers or radar data). Abstracts focusing on models of global-scale processes are also encouraged.