Articles | Volume 28, issue 2
https://doi.org/10.5194/npg-28-257-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/npg-28-257-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
19 May 2021
Research article |
| 19 May 2021
| 19 May 2021
Magnetospheric chaos and dynamical complexity response during storm time disturbance
Irewola Aaron Oludehinwa
CORRESPONDING AUTHOR
Department of Physics, University of Lagos, Lagos, Nigeria
Olasunkanmi Isaac Olusola
Department of Physics, University of Lagos, Lagos, Nigeria
Olawale Segun Bolaji
Department of Physics, University of Lagos, Lagos, Nigeria
Department of Physics, University of Tasmania, Hobart, Australia
Olumide Olayinka Odeyemi
Department of Physics, University of Lagos, Lagos, Nigeria
Abdullahi Ndzi Njah
Department of Physics, University of Lagos, Lagos, Nigeria
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Subject: Bifurcation, dynamical systems, chaos, phase transition, nonlinear waves, pattern formation | Topic: Ionosphere, magnetosphere, planetary science, solar science | Techniques: Big data and artificial intelligence
Ionospheric Chaos in Solar quiet Current due to Sudden Stratospheric Warming Events Across Europe-Africa Sector
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The contributing influence of SSW to regional ionosphere through chaos theory is examined. We found that ionospheric chaos is more pronounced in the European sector compared to Africa sector during SSW. Evidence of orderliness behavior in regional ionosphere of African sector was observed. Finally, we noticed that after the peak phase of SSW, ionospheric chaos is found to be more pronounced.
Cited articles
Akasofu, S. I.: The development of the auroral substorm, Planet. Space Sci.,
12, 273–282, https://doi.org/10.1016/0032-0633(64)90151-5, 1964.
Baker, D. N. and Klimas, A. J.: The evolution of weak to strong geomagnetic
activity: An interpretation in terms of deterministic chaos, J. Geophys.
Res. Lett., 17, 41–44,
https://doi.org/10.1029/GL017i001p00041, 1990.
Balasis, G., Daglis, I. A., Kapiris, P., Mandea, M., Vassiliadis, D., and Eftaxias, K.: From pre-storm activity to magnetic storms: a transition described in terms of fractal dynamics, Ann. Geophys., 24, 3557–3567, https://doi.org/10.5194/angeo-24-3557-2006, 2006.
Balasis, G., Daglis, I. A., Papadimitriou, C., Kalimeri, M., Anastasiadis, A.,
and Eftaxias, K.: Investigating dynamical complexity in the magnetosphere
using various entropy measures, J. Geophys. Res., 114, A0006, https://doi.org/10.1029/2008JA014035, 2009.
Balasis, G., Daglis, I. A., Anastasiadia, A., and Eftaxias, K.: Detection of
dynamical complexity changes in Dst time series using entropy concepts and
rescaled range analysis, The Dynamics Magnetosphere, edited by: Liu, W. and Fujimoto, M., IAGA Special Sopron Book Series 3, Springer Science+Business
Media B. V., https://doi.org/10.1007/978-94-007-0501-2_12, 2011.
Balikhin, M. A., Boynton, R. J., Billings, S. A., Gedalin, M., Ganushkina, N.,
and Coca, D.: Data based quest for solar wind-magnetosphere coupling
function, Geophys. Res. Lett, 37, L24107, https://doi.org/10.1029/2010GL045733, 2010.
Burton, R. K., McPherron, R. L., and Russell, C. T.: An empirical relationship between interplanetary conditions and Dst, J. Geophys. Res.,
80, 4204–4214, https://doi.org/10.1029/JA080i031p04204, 1975.
Consolini, G.: Emergence of dynamical complexity in the Earth's
magnetosphere, in: Machine learning techniques for space weather, edited by: Camporeale, E., Wing, S., and Johnson, J. R., Elsevier, 177–202,
https://doi.org/10.1016/B978-0-12-811788-0.00007-X, 2018.
Cowley, S. W. H.: The earth's magnetosphere: A brief beginner's guide, EOS
Trans. Am. Geophys. Union, 76, 528–529, https://doi.org/10.1029/95EO00322, 1995.
Dessler, A. J. and Parker, E. N.: Hydromagnetic theory of magnetic storm, J.
Geophys. Res, 64, 2239–2259, https://doi.org/10.1029/JZ064i012p02239, 1959.
Donner, R. V., Balasis, G., Stolbova,V., Georgiou, M., Weiderman, M., and
Kurths, J.: Recurrence-based quantification of dynamical complexity in the
earth's magnetosphere at geospace storm time scales, J. Geophys.
Res.-Space, 124, 90–108, https://doi.org/10.1029/2018JA025318, 2019.
Dungey, J. W.: Interplanetary magnetic field and auroral zones,
Phys. Rev. Lett., 6, 47–48, https://doi.org/10.1103/PhysRevLett.6.47, 1961.
Echer, E., Gonzalez, D., and Alves, M.V.: On the geomagnetic effects of
solar wind interplanetary magnetic structures, Space Weather, 4, S06001,
https://doi.org/10.1029/2005SW000200, 2006.
Echer, E., Gonzalez, W. D., Tsurutani, B. T., and Gonzalez, A. L. C.:
Interplanetary conditions causing intense geomagnetic storms (
Feldstein, Y. I., Levitin, A. E., Kozyra, J. U., Tsurutani, B. T., Prigancova, L., Alperovich, L., Gonzalez, W. D., Mall, U., Alexeev, I. I., Gromava, L. I.,
and Dremukhina, L. A.: Self-consistent modelling of the large-scale
distortions in the geomagnetic field during the 24–27 September 1998 major
geomagnetic storm, J. Geophys. Res., 110, A11214, https://doi.org/10.1029/2004JA010584, 2005.
Feldstein, Y. I., Popov, V. A., Cumnock, J. A., Prigancova, A., Blomberg, L. G., Kozyra, J. U., Tsurutani, B. T., Gromova, L. I., and Levitin, A. E.: Auroral electrojets and boundaries of plasma domains in the magnetosphere during magnetically disturbed intervals, Ann. Geophys., 24, 2243–2276, https://doi.org/10.5194/angeo-24-2243-2006, 2006.
Fraser, A. M.: Using mutual information to estimate metric entropy, in: Dimension and Entropies in chaotic system, edited by:
Mayer-Kress, G., Springer
series in Synergetics, 32. Springer, Berlin, Heidelberg, 82–91, https://doi.org/10.1007/978-3-642-71001-8_11, 1986.
Fraser, A. M. and Swinney, H. L.: Independent coordinates for strange
attractors from mutual information, Phys. Rev. A, 33, 1134–1140, https://doi.org/10.1103/PhysRevA.33.1134, 1986.
Gautama, T., Mandic, D. P., and Hulle, M. M. V.: The delay vector variance
method for detecting determinism and nonlinearity in time series, Phys. D,
190, 167–176, https://doi.org/10.1016/j.physd.2003.11.001, 2004.
Gonzalez, W. D. and Tsurutani, B. T.: Criteria of interplanetary parameters
causing intense magnetic storm (
Gonzalez, W. D., Tsurutani, B. T., Gonalez, A. L. C., Smith, E. J., Tang, F., and
Akasofu, S. I.: Solar wind-magnetosphere coupling during intense magnetic
storms (1978–1979), J. Geophys. Res., 94, 8835–8851, https://doi.org/10.1029/JA094iA07p08835,
1989.
Gonzalez, W. D., Joselyn, J. A., Kamide, Y., Kroehl, H. W., Rostoker, G.,
Tsurutani, B. T., and Vasyliunas, V. M.: What is a geomagnetic storm?, J.
Geophys. Res.-Space, 99, 5771–5792, https://doi.org/10.1029/93JA02867,
1994.
Hajra, R. and Tsurutani, B. T.: Interplanetary shocks inducing
magnetospheric supersubstorms (SML < −2500 nT): unusual auroral
morphologies and energy flow, Astrophys. J., 858, 123,
https://doi.org/10.3847/1538-4357/aabaed, 2018.
Hajra, R., Echer, E., Tsurutani, B. T., and Gonazalez, W. D.: Solar cycle
dependence of High-intensity Long-duration Continuous AE activity (HILDCAA)
events, relativistic electron predictors? (2013), J. Geophys. Res.-Space, 118,
5626–5638, https://doi.org/10.1002/jgra.50530, 2013.
Imtiaz, A.: Detection of nonlinearity and stochastic nature in time series
by delay vector variance method, Int. J. Eng. Tech., 10, 11–16, 2010.
Jaksic, V., Mandic, D. P., Ryan, K., Basu, B., and Pakrashi V.: A
Comprehensive Study of the Delay Vector Variance Method for Quantification
of Nonlinearity in dynamical Systems, R. Soc. OpenSci., 3, 150493, https://doi.org/10.1098/rsos.150493, 2016.
Johnson, J. R. and Wing, S.: A solar cycle dependence of nonlinearity in
magnetospheric activity, J. Geophys. Res., 110, A04211, https://doi.org/10.1029/2004JA010638, 2005.
Kannathal, N., Choo, M. L., Acharya, U. R., and Sadasivan, P. K.: Entropies for detecting of epilepsy in EEG, Comput. Meth. Prog. Bio., 80, 187–194, https://doi.org/10.1016/j.cmpb.2005.06.012, 2005.
Kennel, M. B., Brown, R., and Abarbanel, H. D. I.: Determining
embedding dimension for phase-space reconstruction using a geometrical
construction, Phys. Rev. A, 45, 3403–3411, https://doi.org/10.1103/PhysRevA.45.3403, 1992.
King, J. H. and Papitashvili, N. E.: Solar wind spatial scales in and comparisons of hourly Wind and ACE plasma and magnetic field data, J. Geophys. Res., 110, A02209, https://doi.org/10.1029/2004JA010649, 2004 (data available at: https://omniweb.gsfc.nasa.gov/form/dx1.html, last access: 15 May 2021).
Klimas, A. J., Vassilliasdis, D., Baker, D. N., and Roberts, D. A.: The organized
nonlinear dynamics of the magnetosphere, J. Geophys. Res., 101,
13089–13113, https://doi.org/10.1029/96JA00563, 1996.
Kozyra, J. U., Crowley, G., Emery, B. A., Fang, X., Maris, G., Mlynczak, M. G.,
Niciejewski, R. J., Palo, S. E., Paxton, L. J., Randall, C. E., Rong, P. P.,
Russell, J. M., Skinner, W., Solomon, S. C., Talaat, E. R., Wu, Q., and Yee,
J. H.: Response of the Upper/Middle Atmosphere to Coronal Holes and Powerful
High-Speed Solar Wind Streams in 2003, Geoph. Monog. Series, 167, 319–340,
https://doi.org/10.1029/167GM24, 2006.
Kugiumtzis, D.: Test your surrogate before you test your nonlinearity, Phys.
Rev. E, 60, 2808–2816, https://doi.org/10.1103/PhysRevE.60.2808, 1999.
Liou, K., Newell, P. T., Zhang, Y.-L., and Paxton, L. J.: Statistical comparison
of isolated and non-isolated auroral substorms, J. Geophys. Res.-Space, 118, 2466–2477, https://doi.org/10.1002/jgra.50218, 2013.
Lorenz, E. N.: Determining nonperiodic flow, J. Atmos. Sci., 20, 130–141, https://doi.org/10.1177/0309133315623099, 1963.
Love, J. J. and Gannon, J. L.: Revised Dst and the epicycles of magnetic disturbance: 1958–2007, Ann. Geophys., 27, 3101–3131, https://doi.org/10.5194/angeo-27-3101-2009, 2009.
Mandic, D. P., Chen, M., Gautama, T., Van Hull, M. M., and Constantinides, A.:
On the Characterization of the Deterministic/Stochastic and Linear/Nonlinear
Nature of Time Series, Proc. R. Soc., A464, 1141–1160, https://doi.org/10.1098/rspa.2007.0154, 2007.
Mañé, R.: On the dimension of the compact invariant sets of certain
nonlinear maps, in: Dynamical Systems and Turbulence, editd by: Rand, D. and Young, L. S., Warwick 1980, Springer, Berlin, Heidelberg, Lecture Notes in Mathematics, 898, 230–242, https://doi.org/10.1007/BFb0091916, 1981.
Mckinley, R. A., Mclntire, L. K., Schmidt, R., Repperger, D. W., and Caldwell,
J. A.: Evaluation of Eye Metrics as a Detector of Fatigue, Human factor, 53, 403–414, https://doi.org/10.1177/0018720811411297, 2011.
Mendes, O., Domingues, M. O., Echer, E., Hajra, R., and Menconi, V. E.: Characterization of high-intensity, long-duration continuous auroral activity (HILDCAA) events using recurrence quantification analysis, Nonlin. Processes Geophys., 24, 407–417, https://doi.org/10.5194/npg-24-407-2017, 2017.
Meng, C. I., Tsurutani, B., Kawasaki, K., and Akasofu, S. I.:
Cross-correlation analysis of the AE index and the interplanetary magnetic
field Bz component, J. Geophys. Res., 78, 617–629, https://doi.org/10.1029/JA078i004p00617, 1973.
Meng, X., Tsurutani, B. T., and Mannucci, A. J.: The solar and
interplanetary causes of superstorms (minimum
Moore, C. and Marchant, T.: The approximate entropy concept extended to three
dimensions for calibrated, single parameter structural complexity
interrogation of volumetric images, Phys. Med. Biol.,
62, 6092–6107, https://doi.org/10.1088/1361-6560/aa75b0, 2017.
Oludehinwa, I. A., Olusola, O. I., Bolaji, O. S., and Odeyemi, O. O.:
Investigation of nonlinearity effect during storm time disturbance, Adv.
Space. Res, 62, 440–456, https://doi.org/10.1016/j.asr.2018.04.032, 2018.
Pavlos, G. P.: The magnetospheric chaos: a new point of view of the
magnetospheric dynamics. Historical evolution of magnetospheric chaos
hypothesis the past two decades, Conference Proceeding of the 2nd
Panhellenic Symposium, 26–29 April 1994, Democritus University, Thrace, Greece, 1994.
Pavlos, G. P.: Magnetospheric dynamics and Chaos theory, arXiv [preprint], arXiv:1203.5559, 26 March 2012.
Pavlos, G. P., Rigas, A. G., Dialetis, D., Sarris, E. T., Karakatsanis, L. P.,
and Tsonis, A. A.: Evidence of chaotic dynamics in the outer solar plasma and
the earth magnetosphere. Chaotic dynamics: Theory and Practice, edited by:
Bountis, T., Plenum Press, New York, USA, 327–339,
https://doi.org/10.1007/978-1-4615-3464-8_30, 1992.
Pavlos, G. P., Athanasiu, M. A., Diamantidis, D., Rigas, A. G., and Sarris, E. T.: Comments and new results about the magnetospheric chaos hypothesis, Nonlin. Processes Geophys., 6, 99–127, https://doi.org/10.5194/npg-6-99-1999, 1999.
Pincus, S. M.: Approximate entropy as a measure of system complexity,
P. Natl. Acad. Sci. USA, 88, 2297–2301, https://doi.org/10.1073/pnas.88.6.2297, 1991.
Pincus, S. M. and Goldberger, A. L.: Physiological time series analysis: what
does regularity quantify, Am. J. Physiol., 266,
1643–1656, https://doi.org/10.1152/ajpheart.1994.266.4.H1643, 1994.
Pincus, S. M. and Kalman, E. K.: Irregularity, volatility, risk, and
financial market time series, P. Natl. Acad.
Sci. USA, 101, 13709–13714, https://doi.org/10.1073/pnas.0405168101, 2004.
Prabin Devi, S., Singh, S. B., and Surjalal Sharma, A.: Deterministic dynamics of the magnetosphere: results of the 0–1 test, Nonlin. Processes Geophys., 20, 11–18, https://doi.org/10.5194/npg-20-11-2013, 2013.
Price, C. P. and Prichard, D.: The Non-linear response of the magnetosphere:
30 October, 1978, Geophys. Res. Lett., 20, 771–774, https://doi.org/10.1029/93GL00844, 1993.
Price, C. P., Prichard, D., and Bischoff, J. E.: Nonlinear input/output
analysis of the auroral electrojet index, J. Geophys. Res.,
99, 13227–13238, https://doi.org/10.1029/94JA00552, 1994.
Richardson, I. G. and Cane, H. V.: Geoeffectiveness (Dst and Kp) of interplanetary coronal mass ejections during 1995–2009 and
implication for storm forecasting, Space Weather, 9, S07005,
https://doi.org/10.1029/2011SW000670, 2011.
Russell, C. T.: Solar wind and Interplanetary Magnetic Field: A Tutorial,
Space Weather, Geophysical Monograph, 125, 73–89, https://doi.org/10.1029/GM125p0073, 2001.
Russell, C. T., McPherron, R. L., and Burton, R. K.: On the cause of
geomagnetic storms, J. Geophys. Res., 79, 1105–1109, https://doi.org/10.1029/JA079i007p01105, 1974.
Shan, L.-H., Goertz, C. K., and Smith, R. A.: On the embedding-dimension analysis of AE and AL time series. Geophys. Res. Lett., 18, 1647–1650, https://doi.org/10.1029/91GL01612, 1991.
Shujuan, G. and Weidong, Z.: Nonlinear feature comparison of EEG using
correlation dimension and approximate entropy, 3rd international conference
on biomedical engineering and informatics, 16–18 October 2010, Yantai, China, IEEE, https://doi.org/10.1109/BMEI.2010.5639306, 2010.
Strogatz, S. H.: Nonlinear dynamics and chaos with Application to physics,
Biology, chemistry and Engineering, John Wiley & Sons, New York, USA, 1994.
Sugiura, M.: Hourly Values of equatorial Dst for the IGY, Ann. Int. Geophys. Year, 35, 9–45, 1964
Sugiura, M. and Kamei T.: Equatorial Dst index 1957–1957–1986, in: IAGA bull 40. International Service of Geomagnetic Indices, edited by: Berthelier, A. and Menvielle, M., Saint-Maur-des-Fosses, France, 1991.
Takens, F.: Detecting Strange Attractors in Turbulence in Dynamical Systems,
in: Dynamical systems and Turbulence, Warwick 1980.
Lecture Notes in mathematics, Rand, D. and Young, L. S., Springer, Berlin, Heidelberg, vol. 898, https://doi.org/10.1007/BFb0091924, 1981.
Theiler, J., Eubank, S., Longtin, A., Galdrikian, B., and Farmer,
J. D.: Testing for nonlinearity in time series: The method of surrogate data,
Phys. D, 58, 77–94, https://doi.org/10.1016/0167-2789(92)90102-S, 1992.
Tsurutani, B. T. and Gonazalez, W. D.: The cause of High-intensity Long duration
Continuous AE activity (HILDCAAs): Interplanetary Alfven trains, Planet.
Space Sci., 35, 405–412, https://doi.org/10.1016/0032-0633(87)90097-3, 1987.
Tsurutani, B. T. and Hajra, R.: The interplanetary and magnetospheric causes
of geomagnetically induced currents (GICs) > 10A in the Mantsala
finland Pipeline: 1999 through 2019, J. Space Weather Space Clim., 11, 32,
https://doi.org/10.1051/swsc/2021001, 2021.
Tsurutani, B. T. and Meng, C. I.: Interplanetary magnetic field variations and substorm activity, J. Geophys. Res., 77, 2964–2970, https://doi.org/10.1029/JA077i016p02964, 1972.
Tsurutani, B. T., Gonzalez, W. D., Tang, F., Akasofu, S. I., and Smith, E. J.:
Origin of Interplanetary Southward Magnetic Fields Responsible for Major
Magnetic Storms Near Solar Maximum (1978–1979), J. Geophys. Res., 93, 8519–8531, https://doi.org/10.1029/JA093iA08p08519, 1988.
Tsurutani, B. T., Sugiura, M., Iyemori, T., Goldstein, B. E., Gonazalez, W. D.,
Akasofu, S. I., and Smith, E. J.: The nonlinear response of AE to the IMF Bs
driver: A spectral break at 5 hours, Geophys. Res. Lett.,
17, 279–283, https://doi.org/10.1029/GL017i003p00279, 1990.
Tsurutani, B. T., Gonzalez, A. L. C., Tang, F., Arballo, J. K., and Okada, M.:
Interplanetary origin of geomagnetic activity in the declining phase of the
solar cycle, J. Geophys. Res., 100, 717–733, 1995.
Tsurutani, B. T., Gonzalez, W. D., Lakhina, G. S. and Alex, S.: The extreme
magnetic storm of 1–2 September 1859, J. Geophys. Res., 108, 1268, https://doi.org/10.1029/2002JA009504, 2003.
Tsurutani, B. T., Lakhina, G. S., Verkhoglyadova, O. P., Gonzalez, W. D., Echer, E., and Guarnieri, F. L.: A review of interplanertary discontinuities and their
geomagnetic effects, J. Atmos. Sol.-Terr. Phy., 73, 5–19,
https://doi.org/10.1016/j.jastp.2010.04.001, 2010.
Tsurutani, B. T., Lakhina, G. S., and Hajra, R.: The physics of space weather/solar-terrestrial physics (STP): what we know now and what the current and future challenges are, Nonlin. Processes Geophys., 27, 75–119, https://doi.org/10.5194/npg-27-75-2020, 2020.
Tsutomu, N.: Geomagnetic storms, Journal of communications Research
Laboratory, 49, 3, available at: https://www.nict.go.jp/publication/shuppan/kihou-journal/journal-vol49no3/0305.pdf (last access: 14 May 2021),
2002.
Turner, N. E., Mitchell, E. J., Knipp, D. J., and Emery, B. A.: Energetics of
magnetic storms driven by corotating interaction regions: a study of
geoeffectiveness, Geoph. Monog. Series, 167, 113–124, https://doi.org/10.1029/167GM11, 2006.
Unnikrishnan, K.: Comparison of chaotic aspects of magnetosphere under various physical conditions using AE index time series, Ann. Geophys., 26, 941–953, https://doi.org/10.5194/angeo-26-941-2008, 2008.
Valdivia, J. A., Sharma, A. S., and Papadopoulos, K.: Prediction of magnetic
storms by nonlinear models, Geophys. Res. Lett., 23, 2899–2902,
https://doi.org/10.1029/96GL02828, 1996.
Valdivia, J. A., Rogan, J., Munoz, V., Gomberoff, L., Klimas, A.,
Vassilliasdis, D., Uritsky, V., Sharma, S., Toledo, B., and Wastaviono, L.: The
magnetosphere as a complex system, Adv. Space. Res., 35, 961–971, https://doi.org/10.1016/j.asr.2005.03.144, 2005.
Vassiliadis, D.: Systems theory for geospace plasma dynamics, Rev. Geophys.,
44, RG2002, https://doi.org/10.1029/2004RG000161, 2006.
Vassilliadis, D. V., Sharma, A. S., Eastman, T. E., and Papadopoulou, K.:
Low-dimensional chaos in magnetospheric activity from AE time series, J.
Geophys. Res. Lett, 17, 1841–1844, https://doi.org/10.1029/GL017i011p01841, 1990.
Vassilliadis, D., Sharma, A. S., and Papadopoulos, K.: Lyapunov exponent
of magnetospheric activity from AL time series, J. Geophys.
Lett., 18, 1643–1646, https://doi.org/10.1029/91GL01378, 1991.
Vassiliadis, D., Klimas, A. J., Valdivia, J. A., and Baker, D. N.: The geomagnetic
response as a function of storm phase and amplitude and solar wind electric
field, J. Geophys. Res., 104, 24957–24976, https://doi.org/10.1029/1999JA900185, 1999.
Wallot, S. and Monster, D.: Calculation of Average Mutual Information (AMI) and
False Nearest Neigbhours (FNN) for the estimation of embedding parameters of
multidimensional time series in MATLAB, Front. Physchol., 9, 1679, https://doi.org/10.3389/fpsyg.2018.01679, 2018.
Wolf, A., Swift, J. B., Swinney, H. L., and Vastano, J. A.: Determining
Lyapunov exponents from a time series, Phys. D, 16, 285–317,
https://doi.org/10.1016/0167-2789(85)90011-9, 1985.
World Data Center for Geomagnetism, Kyoto, Nose, M., Iyemori, T., Sugiura, M., and Kamei, T.: Geomagnetic Dst index, https://doi.org/10.17593/14515-74000, 2015.
Yurchyshyn, V., Wang, H., Abramenko, V., Spirock, T., and Krucker, S.: Magnetic field, Hα and Rhessi Observations of the 2002 July 23 Gamma-ray, Astrophys. J., 605, 546–553, https://doi.org/10.1086/382142, 2004.
Short summary
The MLE and ApEn values of the Dst indicate that chaotic and dynamical complexity responses are high during minor geomagnetic storms, reduce at moderate geomagnetic storms and decline further during major geomagnetic storms.
However, the MLE and ApEn values obtained from solar wind electric field (VBs) indicate that chaotic and dynamical complexity responses are high with no significant difference between the periods that are associated with minor, moderate and major geomagnetic storms.
The MLE and ApEn values of the Dst indicate that chaotic and dynamical complexity responses are...
