Articles | Volume 39, issue 5
https://doi.org/10.5194/angeo-39-861-2021
https://doi.org/10.5194/angeo-39-861-2021
Regular paper
 | 
08 Oct 2021
Regular paper |  | 08 Oct 2021

Unsupervised classification of simulated magnetospheric regions

Maria Elena Innocenti, Jorge Amaya, Joachim Raeder, Romain Dupuis, Banafsheh Ferdousi, and Giovanni Lapenta

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Subject: Magnetosphere & space plasma physics | Keywords: Magnetospheric configuration and dynamics
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Cited articles

Amaya, J., Dupuis, R., Innocenti, M. E., and Lapenta, G.: Visualizing and Interpreting Unsupervised Solar Wind Classifications, Front. Astron. Space Sci., 7, 66, https://doi.org/10.3389/fspas.2020.553207, 2020. a, b, c, d, e, f
Anderson, B. J., Korth, H., Welling, D. T., Merkin, V. G., Wiltberger, M. J., Raeder, J., Barnes, R. J., Waters, C. L., Pulkkinen, A. A., and Rastaetter, L.: Comparison of predictive estimates of high-latitude electrodynamics with observations of global-scale Birkeland currents, Space Weather, 15, 352–373, https://doi.org/10.1002/2016sw001529, 2017. a
Angelopoulos, V.: The THEMIS mission, in: The THEMIS mission, 5–34, Springer, New York, NY, 2009. a
Argall, M. R., Small, C. R., Piatt, S., Breen, L., Petrik, M., Kokkonen, K., Barnum, J., Larsen, K., Wilder, F. D., Oka, M., Paterson, W. R., Torbert, R. B., Ergun, R. E., Phan, T., Giles, B. L., and Burch, J. L.: MMS SITL Ground Loop: Automating the Burst Data Selection Process, Front. Astron. Space Sci., 7, 54, https://doi.org/10.3389/fspas.2020.00054, 2020. a, b, c
Armstrong, J. A. and Fletcher, L.: Fast solar image classification using deep learning and its importance for automation in solar physics, Solar Phys., 294, 80, https://doi.org/10.1007%2Fs11207-019-1473-z, 2019. a
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Short summary
Spacecraft missions do not always record observations at the highest possible resolution, and the so-called burst mode is switched on only occasionally. It is of paramount importance that processes of interest are sampled in burst mode. At the moment, many missions rely on a scientist in the loop, who decides when to trigger burst mode by looking at the preview data. Our work constitutes a first step towards making this decision automatic to improve mission operations and decrease human bias.