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Session Chair: Eric Frank Donovan Session Chair: Pierre Langlois
Swarm-Aurora: Identifying Auroral Conjunctions Using an Online and Offline Cross-Platform Set of Tools
Darren Chaddock1, Eric Donovan1, Emma Spanswick1, David Knudsen1, Harald Frey2, Kirsti Kauristie3, Noora Partamies4, Brian Jackel1, Megan Gillies1, Poul Erik Holmdahl Olsen5
1University of Calgary, Canada; 2University of California Berkeley; 3Finnish Meteorological Institute; 4The University Centre in Svalbard; 5DTU Space
In recent years there has been a dramatic increase in ground-based auroral imaging systems. These include the continent-wide THEMIS-ASI network, and imagers operated by other programs including GO-Canada, MIRACLE, AGO, OMTI, and more. In the near future, a new Canadian program called TREx will see the deployment of new narrow-band ASIs that will provide multi-wavelength imaging across Western Canada. At the same time, there is an unprecedented fleet of international spacecraft probing geospace at low and high altitudes. We are now in the position to simultaneously observe the magnetospheric drivers of aurora, observe in situ the waves, currents, and particles associated with MI coupling, and the conjugate aurora. Whereas a decade ago, a single magnetic conjunction between one ASI and a low altitude satellite was a relatively rare event, we now have a plethora of triple conjunctions between imagers, low-altitude spacecraft, and near-equatorial magnetospheric probes. But with these riches comes a new level of complexity. It is often difficult to identify the many useful conjunctions for a specific line of inquiry from the multitude of conjunctions where the geospace conditions are often not relevant and/or the imaging is compromised by clouds, moon, or other factors.
Swarm-Aurora was designed to facilitate and drive the use of Swarm in situ measurements in auroral science. The project seeks to build a bridge between the Swarm science community, Swarm data, and the complimentary auroral data and community. Swarm-Aurora (http://swarmaurora.com) incorporates a set of web-based and stand-alone offline tools which provides access to quick-look summary data for a large array of instruments, with Swarm in situ and ground-based ASI data as the primary focus. These cross-platform tools allow researchers to quickly and efficiently browse Swarm and ASI data to identify auroral events of interest to them. Providing interaction with this data in this manner drastically reduces the time needed to do a preliminary survey of Swarm and ground-based instruments for investigating auroral phenomena. In this paper, we will discuss the various sets of tools we have developed and our path moving forward.
New Insight into Auroral Arc Microphysics from e-POP
Gareth Perry1, Yanyang Shen1, Gordon James1, Andrew Howarth1, Leroy Cogger1, David Knudsen1, David Miles2, Andrew Yau1
1University of Calgary, Canada; 2University of Alberta, Canada
Using a full complement of instruments onboard the Enhanced Polar Outflow Probe (e-POP) on the CAScade, Smallsat and IOnospheric Polar Explorer (CASSIOPE) spacecraft, we investigate the plasma and auroral dynamics of an active auroral arc identified using e-POP’s Fast Auroral Imager (FAI). As CASSIOPE approached, crossed, and retreated from the arc, its International Geomagnetic Reference Field (IGRF) footprint remained within the FAI’s field-of-view. Because of this, we are able to study the interconnection of the optical, plasma, and electromagnetic properties of the arc.
At the time of closest approach to the arc CASSIOPE was located at 457 km altitude. The e-POP MaGnetic Field instrument (MGF) observed magnetic field perturbations indicative of structures of field-aligned currents coincident with the arc. Data from e-POP’s Imaging and Rapid-Scanning Mass Spectrometer (IRM) show a highly structured, O+ dominated plasma in the vicinity of the arc, with a strong asymmetry in vertical plasma flows on either side of the arc. Additionally, measurements from e-POP’s Radio Receiver Instrument (RRI) show intensified auroral hiss signatures at the location of the arc, and a region of strong sub-kHz radio wave activity poleward of the arc. Meanwhile, data from e-POP’s Suprathermal Electron Imager (SEI), which was operating in ion-mode, displays ion heating signatures near the poleward edge of the arcindicates the possibility of significant ion heating at the location of the arc. We assimilate e-POP’s highly-resolved contemporaneous dataset in order to provide new and compelling insight into the microphysics of dynamic magnetosphere-ionosphere coupling processes.
Inferring Ionospheric Convection from Sequences of Auroral Images: A Complement to Swarm EFI
Eric M. Grono1, Eric Donovan1, Kyle R. Murphy2, Bing Yang1, Emma Spanswick1, Dave Knudsen1
1University of Calgary, Canada; 2NASA Goddard Space Flight Center, Greenbelt, MD, United States
Patchy Pulsating Aurora (PPA) is frequently observed in the evening and morning sector auroral oval. While the precipitating electrons span a wide range of energies, there is increasing evidence that the shape of the PPA patches is controlled by structures in the near-equatorial cold plasma; structures in PPA are thought to move with ionospheric convection, for example. If this is true, then Swarm EFI observations of ionospheric convection will be significantly augmented by velocity maps inferred from auroral image sequences (e.g., from THEMIS ASI).
While developing a system of automatically processing the immense and rapidly growing amount auroral image data to extract convection, it became clear that the aurora referred to as PPA is at least two separate phenomena. One of these types of aurora is comprised of patches that move with convection, while the other exhibits profoundly different spatio-temporal behaviour and must arise from a fundamentally different electromagnetic/Alfvénic process.
In this talk, we will demonstrate the technique used to separate the two types of PPA, and an initial analysis of the differences between the phenomena. A key result is that the two types of PPA have different MLT distributions which may provide a clue as to their nature. The results of pattern recognition and image classification studies that identify aurora and PPA automatically will be presented, and we will demonstrate how to infer velocities of these structures that can augment convection measurements obtained via Swarm EFI observations.