Baker, D., Riesberg, L., Pankratz, C., Panneton, R., Giles, B., Wilder, F., and
Ergun, R.: Magnetospheric multiscale instrument suite operations and data
system, Space Sci. Rev., 199, 545–575, 2016. a
Bakrania, M. R., Rae, I. J., Walsh, A. P., Verscharen, D., and Smith, A. W.:
Using dimensionality reduction and clustering techniques to classify space
plasma regimes, Front. Astron. Space Sci., 7, 80,
https://doi.org/10.3389/fspas.2020.593516, 2020.
a
Balasis, G., Aminalragia-Giamini, S., Papadimitriou, C., Daglis, I. A.,
Anastasiadis, A., and Haagmans, R.: A machine learning approach for automated
ULF wave recognition, J. Space Weather Spac., 9, A13,
https://doi.org/10.1051/swsc/2019010,
2019.
a
Berchem, J., Raeder, J., and Ashour-Abdalla, M.: Reconnection at the
magnetospheric boundary: Results from global MHD simulations, in: Physics
of the Magnetopause, edited by: Sonnerup, B. U. and Song, P.,
AGU Geophysical Monograph, 90, 205,
https://doi.org/10.1029/GM090p0205, 1995.
a
Breuillard, H., Dupuis, R., Retino, A., Le Contel, O., Amaya, J., and Lapenta,
G.: Automatic Classification of Plasma Regions in Near-Earth Space With
Supervised Machine Learning: Application to Magnetospheric Multi Scale
2016–2019 Observations, Front. Astronom. Space Sci., 7, 55,
https://doi.org/10.3389/fspas.2020.00055, 2020.
a
Burch, J., Moore, T., Torbert, R., and Giles, B.: Magnetospheric multiscale
overview and science objectives, Space Sci. Rev., 199, 5–21, 2016. a
Camporeale, E.: The challenge of machine learning in space weather: Nowcasting
and forecasting, Space Weather, 17, 1166–1207, 2019. a
Connor, H. K., Zesta, E., Fedrizzi, M., Shi, Y., Raeder, J., Codrescu, M. V.,
and Fuller-Rowell, T. J.: Modeling the ionosphere-thermosphere response to a
geomagnetic storm using physics-based magnetospheric energy input:
OpenGGCM-CTIM results, J. Space Weather Spac., 6,
A25,
https://doi.org/10.1051/swsc/2016019, 2016.
a
da Silva, D., Barrie, A., Shuster, J., Schiff, C., Attie, R., Gershman, D., and
Giles, B.: Automatic Region Identification over the MMS Orbit by Partitioning
nT space, arXiv preprint arXiv:2003.08822, 2020. a
Escoubet, C. P., Fehringer, M., and Goldstein, M.: Introduction:
The Cluster mission, Ann. Geophys., 19, 1197–1200,
https://doi.org/10.5194/angeo-19-1197-2001, 2001.
a
Ferdousi, B. and Raeder, J.: Signal propagation time from the magnetotail to
the ionosphere: OpenGGCM simulation, J. Geophys. Res.-Space
Phys., 121, 6549–6561, 2016. a
Florios, K., Kontogiannis, I., Park, S.-H., Guerra, J. A., Benvenuto, F.,
Bloomfield, D. S., and Georgoulis, M. K.: Forecasting solar flares using
magnetogram-based predictors and machine learning, Solar Phys., 293, 28,
https://doi.org/10.1007/s11207-018-1250-4,
2018.
a
Ge, Y. S., Raeder, J., Angelopoulos, V., Gilson, M. L., and Runov, A.:
Interaction of dipolarization fronts within multiple bursty bulk flows in
global MHD simulations of a substorm on 27 February 2009, J.
Geophys. Res., 116, A00I23,
https://doi.org/10.1029/2010JA015758, 2011.
a
Kohonen, T.: Self-organized formation of topologically correct feature maps,
Biol. Cybern., 43, 59–69, 1982. a
Kohonen, T.: MATLAB Implementations and Applications of the Self-Organizing
Map, Unigrafia Oy, Helsinki, Finland, 2014.
a,
b,
c,
d,
e
Laakso, H., Perry, C., McCaffrey, S., Herment, D., Allen, A., Harvey, C.,
Escoubet, C., Gruenberger, C., Taylor, M., and Turner, R.: Cluster active
archive: Overview, The cluster active archive, in: The Cluster Active Archive, Springer Netherlands, Dordrecht, 3–37, 2010. a
Lapenta, G., Zhukov, A., and van Driel-Gesztelyi, L.: Solar Wind at the Dawn of
the Parker Solar Probe and Solar Orbiter Era, Solar Phys., 295, 103,
https://doi.org/10.1007/s11207-020-01670-8, 2020.
a
Lloyd, S.: Least squares quantization in PCM, IEEE transactions on information
theory, 28, 129–137, 1982. a
Love, T., Neukirch, T., and Parnell, C. E.: Analyzing AIA Flare Observations
Using Convolutional Neural Networks, Front. Astron. Space
Sci., 7, 34,
https://doi.org/10.3389/fspas.2020.00034, 2020.
a
Millas, D., Innocenti, M. E., Laperre, B., Raeder, J., Poedts, S., and Lapenta,
G.: Domain of Influence Analysis: Implications for Data Assimilation in Space
Weather Forecasting, Front. Astron. Space Sci., 7, 73,
https://doi.org/10.3389/fspas.2020.571286, 2020.
a
Moretto, T., Vennerstrom, S., Olsen, N., Rastaetter, L., and Raeder, J.: Using
global magnetospheric models for simulation and interpretation of SWARM
external field measurements, Earth Planets Space, 58, 439–449, 2006. a
Nguyen, G., Aunai, N., Michotte de Welle, B., Jeandet, A., and Fontaine, D.: Automatic detection of the Earth Bow Shock and Magnetopause from in-situ data with machine learning, Ann. Geophys. Discuss. [preprint],
https://doi.org/10.5194/angeo-2019-149, 2019.
a
Nishizuka, N., Sugiura, K., Kubo, Y., Den, M., Watari, S., and Ishii, M.: Solar
flare prediction model with three machine-learning algorithms using
ultraviolet brightening and vector magnetograms, Astrophys. J.,
835, 156,
https://doi.org/10.3847/1538-4357/835/2/156, 2017.
a
Olshevsky, V., Khotyaintsev, Y. V., Divin, A., Delzanno, G. L., Anderzen, S.,
Herman, P., Chien, S. W., Avanov, L., and Markidis, S.: Automated
classification of plasma regions using 3D particle energy distribution, arXiv
preprint arXiv:1908.05715, 2019. a
Raeder, J.: Global Magnetohydrodynamics – A Tutorial, in: Space
Plasma Simulation, edited by: Büchner, J., Dum, C. T., and Scholer, M.,
Springer Verlag, Berlin Heidelberg New York,
https://doi.org/10.1007/3-540-36530-3_11,
2003.
a,
b
Raeder, J., McPherron, R. L., Frank, L. A., Paterson, W. R., Sigwarth, J. B.,
Lu, G., Singer, H. J., Kokubun, S., Mukai, T., and Slavin, J. A.: Global
simulation of the Geospace environment modeling substorm challenge event,
J. Geophys. Res., 106, 381,
https://doi.org/10.1029/2000JA000605, 2001a.
a
Raeder, J., Wang, Y. L., Fuller-Rowell, T. J., and Singer, H. J.: Global
simulation of space weather effects of the Bastille Day storm, Solar
Phys., 204, 325, 2001b. a
Raeder, J., Zhu, P., Ge, Y., and Siscoe, G. L.: OpenGGCM Simulation of a
Substorm: Axial Tail Instability and Ballooning Mode Preceding Substorm
Onset, J. Geophys. Res., 115, A00l16,
https://doi.org/10.1029/2010JA015876, 2010.
a
Raptis, S., Aminalragia-Giamini, S., Karlsson, T., and Lindberg, M.:
Classification of Magnetosheath Jets Using Neural Networks and High
Resolution OMNI (HRO) Data, Front. Astron. Space Sci., 7, 24,
https://doi.org/10.3389/fspas.2020.00024, 2020.
a
Satopaa, V., Albrecht, J., Irwin, D., and Raghavan, B.: Finding a
“Kneedle” in a Haystack: Detecting Knee Points in System Behavior, in: 2011
31st International Conference on Distributed Computing Systems Workshops, 20–24 June 2011, Minneapolis, MN, USA,
166–171, 2011. a
Shi, Q. Q., Hartinger, M., Angelopoulos, V., Tian, A., Fu, S., Zong, Q.-G.,
Weygand, J. M., Raeder, J., Pu, Z., Zhou, X., Dunlop, M., Liu, W., Zhang, H.,
Yao, Z., and Shen, X.: Solar wind pressure pulse-driven magnetospheric
vortices and their global consequences, J. Geophys. Res.-Space Phys., 119, 4274–4280,
https://doi.org/10.1002/2013ja019551, 2014.
a
Shlens, J.: A tutorial on principal component analysis, arXiv preprint
arXiv:1404.1100, 2014. a
Stone, E. C., Frandsen, A., Mewaldt, R., Christian, E., Margolies, D., Ormes,
J., and Snow, F.: The advanced composition explorer, Space Sci. Rev.,
86, 1–22, 1998. a
Vennerstrom, S., Moretto, T., Rastaetter, L., and Raeder, J.: Field-aligned
currents during northward interplanetary field: Morphology and causes,
J. Geophys. Res., 110, A06205,
https://doi.org/10.1029/2004JA010802, 2005.
a
Vettigli, G.: MiniSom: minimalistic and NumPy-based implementation of the Self
Organizing Map, gitHub, available at:
https://github.com/JustGlowing/minisom/, last access: 1 October 2021. a
Zhou, X.-Z., Ge, Y. S., Angelopoulos, V., Runov, A., Liang, J., Xing, X.,
Raeder, J., and Zong, Q.-G.: Dipolarization fronts and associated auroral
activities: 2. Acceleration of ions and their subsequent behavior, J.
Geophys. Res.-Space Phys., 117, 1,
https://doi.org/10.1029/2012ja017677,
2012.
a
Zhu, P., Raeder, J., Germaschewski, K., and Hegna, C. C.: Initiation of ballooning instability in the near-Earth plasma sheet prior to the 23 March 2007 THEMIS substorm expansion onset, Ann. Geophys., 27, 1129–1138,
https://doi.org/10.5194/angeo-27-1129-2009, 2009.
a