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Annales Geophysicae An open-access journal of the European Geosciences Union
Ann. Geophys., 35, 777-784, 2017
https://doi.org/10.5194/angeo-35-777-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Regular paper
03 Jul 2017
Tracking patchy pulsating aurora through all-sky images
Eric Grono1, Eric Donovan1, and Kyle R. Murphy2 1University of Calgary, Calgary, Alberta, Canada
2NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
Abstract. Pulsating aurora 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 pulsating auroral patches is controlled by structures in near-equatorial cold plasma; these patches appear to move with convection, for example. Given the tremendous and rapidly increasing amount of auroral image data from which the velocity of these patches can be inferred, it is timely to develop and implement techniques for the automatic identification of pulsating auroral patch events in these data and for the automatic determination of the velocity of individual patches from that data. As a first step towards this, we have implemented an automatic technique for determining patch velocities from sequences of images from the Time History of Events and Macroscale Interactions during Substorms (THEMIS) all-sky imager (ASI) and applied it to many pulsating aurora events. Here we demonstrate the use of this technique and present the initial results, including a comparison between ewograms (east–west keograms) and time series of patch position as determined by the algorithm. We discuss the implications of this technique for remote sensing convection in the inner magnetosphere.

Citation: Grono, E., Donovan, E., and Murphy, K. R.: Tracking patchy pulsating aurora through all-sky images, Ann. Geophys., 35, 777-784, https://doi.org/10.5194/angeo-35-777-2017, 2017.
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Short summary
The spatial and temporal evolution of the aurora provides information about plasma dynamics throughout the magnetosphere. The THEMIS all-sky imager network has been operating for over 10 years and has accumulated millions of auroral images. To speed the extraction of information from this dataset, it is desirable to implement automated algorithms to track and classify the aurora. This paper demonstrates an automatic method of extracting the motion of the aurora from sequences of images.
The spatial and temporal evolution of the aurora provides information about plasma dynamics...
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